#          ######################################################################################################
#          #                                      IN THE NAME OF ALLAH                                          #
#          #      STEEL-CONCRETE COMPOSITE PLATE GIRDERS BRIDGE SUPERSTRUCTURE INCREMENTAL DYNAMIC ANALYSIS     #
#          #                     EVALUATION OF AXIAL, SECTION, STRUCTURE DUCTILITY DAMAGE INDEX                 #
#          #----------------------------------------------------------------------------------------------------#
#          #                          THIS PROGRAM WRITTEN BY SALAR DELAVAR QASHQAI                             #
#          #                               EMAIL: salar.d.ghashghaei@gmail.com                                  #
#          ######################################################################################################

# Load the image
def PLOT_IMAGE(image):
    import matplotlib.pyplot as plt
    import matplotlib.image as mpimg
    image = mpimg.imread(image_path)

    # Display the image
    plt.figure(figsize=(30, 16))
    plt.imshow(image)
    plt.axis('off')  # Hide axes
    plt.show()
    
image_path = 'OPENSEES_SINGLE_SPAN_SIMPLY_SUPPORTED_COMPOSITE_BRIDGE_00.png'    
PLOT_IMAGE(image_path)

# BRIDGE IMAGES AND DATA
'https://www.steelconstruction.info/A1_Peterborough_to_Blyth'
# BOOK: Finite Element Analysis and Design of Steel and Steel–Concrete Composite Bridges
'https://www.sciencedirect.com/book/9780124172470/finite-element-analysis-and-design-of-steel-and-steel-concrete-composite-bridges'
# BOOK: Steel-concrete composite bridge design guide
'https://www.nzta.govt.nz/assets/resources/research/reports/525/docs/525.pdf' 
# BOOK: Highway Bridge Superstructure Engineering; LRFD Approaches to Design and Analysis-Narendra Taly-CRC Press
'https://www.routledge.com/Highway-Bridge-Superstructure-Engineering-LRFD-Approaches-to-Design-and-Analysis/Taly/p/book/9781466552180?srsltid=AfmBOoo5LQjvUG7nz6f90vuEZNIAuUnmgXMHTyq3wx7YIGd1y2cAMQtI'
# PAPER: Seismic damage prediction by deterministic methods: Concepts and procedures
'https://onlinelibrary.wiley.com/doi/10.1002/eqe.4290160507'

'https://onlinelibrary.wiley.com/doi/10.1002/eqe.4290160507'

# pip install openseespy
# pip install --upgrade openseespy
# pip install opsvis

#import the os module
import os
import time
import numpy as np
import openseespy.opensees as op
import opsvis as opsv
import matplotlib.pyplot as plt

#to create a directory at specified path with name "Data"
os.mkdir('C:\\OPENSEESPY_SALAR')

---------------------------------------------------------------------------
FileExistsError                           Traceback (most recent call last)
Cell In[16], line 2
      1 #to create a directory at specified path with name "Data"
----> 2 os.mkdir('C:\\OPENSEESPY_SALAR')

FileExistsError: [WinError 183] Cannot create a file when that file already exists: 'C:\\OPENSEESPY_SALAR'

FOLDER_NAME = 'COMPOSITE_BRIDGE_IDA'
dir = f"C:\\OPENSEESPY_SALAR\\{FOLDER_NAME}\\"
if not os.path.exists(dir):
    os.makedirs(dir)

## DELETE ALL FILES IN DIRECTORY 
def DELETE_FOLDER_CONTANTS(folder_path):
    import os
    for filename in os.listdir(folder_path):
        file_path = os.path.join(folder_path, filename)
        try:
            if os.path.isfile(file_path) or os.path.islink(file_path):
                os.unlink(file_path)
        except Exception as e:
            print(f"Failed to delete {file_path}. Reason: {e}")
    print("Deletion done")
   
FOLDER_PATH = f'C:\\OPENSEESPY_SALAR\\{FOLDER_NAME}'  # Specify the folder path
#DELETE_FOLDER_CONTANTS(FOLDER_PATH)

# OUTPUT DATA ADDRESS:
SALAR_DIR = f'C://OPENSEESPY_SALAR//{FOLDER_NAME}//';

def HISROGRAM_BOXPLOT(X, HISTO_COLOR, LABEL):
    import numpy as np
    import matplotlib.pyplot as plt
    X = np.array(X)
    print("-------------------------")
    from scipy.stats import skew, kurtosis
    MINIMUM = np.min(X)
    MAXIMUM = np.max(X)
    #MODE = max(set(X), key=list(X).count)
    MEDIAN = np.quantile(X, .50)#q2
    MEAN = np.mean(X)
    STD = np.std(X)
    q1 = np.quantile(X, .25)
    q3 = np.quantile(X, .75)
    SKEW = skew(X)
    KURT = kurtosis(X)
    #SKEW = (MEAN - MODE) / STD
    #KURT = (np.mean((X - MEAN)**4) / STD**4)
    # Estimate confidence intervals of the output variable
    lower_bound = np.quantile(X, .05)
    upper_bound = np.quantile(X, .95)
    print("Box-Chart Datas: ")
    print(f'Minimum: {MINIMUM:.4f}')
    print(f'First quartile: {q1:.4f}')
    #print(f'Mode: {MODE:.4f}')
    print(f'Median: {MEDIAN:.4f}')
    print(f'Mean: {MEAN:.4f}')
    print(f'Std: {STD:.4f}')
    print(f'Third quartile: {q3:.4f}')
    print(f'Maximum: {MAXIMUM :.4f}')
    print(f'Skewness: {skew(X) :.4f}')
    print(f'kurtosis: {kurtosis(X) :.4f}')
    print(f"90% Confidence Interval: ({lower_bound:.4f}, {upper_bound:.4f})")
    print("-------------------------")

    plt.figure(figsize=(10,6))
    # Plot histogram of data
    count, bins, ignored = plt.hist(X, bins=100, color=HISTO_COLOR, density=True, align='mid')#, edgecolor="black"
    
    # Plot lognormal PDF
    x = np.linspace(min(bins), max(bins), 10000)
    pdf = (np.exp(-(x - MEAN)**2 / (2 * STD**2)) / (STD * np.sqrt(2 * np.pi)))
    plt.plot(x, pdf, linewidth=2, color='r', label="Normal PDF")
    
    # Plot vertical lines for risk measures
    plt.axvline(q1, color="black", linestyle="--", label=f"Quantile 0.25: {q1:.4f}")
    plt.axvline(MEDIAN, color="green", linestyle="--", label=f"Median: {MEDIAN:.4f}")
    plt.axvline(q3, color="black", linestyle="--", label=f"Quantile 0.75: {q3:.4f}")
    #plt.axvline(MODE, color="purple", linestyle="--", label=f"Mode: {MODE:.4f}")
    plt.axvline(MEAN, color="red", linestyle="--", label=f"Mean: {MEAN:.4f}")
    plt.axvline(MEAN-STD, color="blue", linestyle="--", label=f"Mean-Std: {MEAN-STD:.4f}")
    plt.axvline(MEAN+STD, color="blue", linestyle="--", label=f"Mean+Std: {MEAN+STD:.4f}")
    plt.xlabel(LABEL)
    plt.ylabel("Frequency")
    prob = np.sum(X > 0) / len(X)
    plt.title(f"Histogram - Probability of Positive {LABEL} is {100*prob:.2f} %")
    plt.legend()
    #plt.grid()
    plt.show()

    #Plot boxplot with outliers
    plt.figure(figsize=(10,6))
    plt.boxplot(X, vert=0)
    # Write the quartile data on the chart
    plt.text(q1, 1.05, f" Q1: {q1:.4f}")
    plt.text(MEDIAN, 1.1, f" Q2: {MEDIAN:.4f}")
    plt.text(q3, 1.05, f" Q3: {q3:.4f}")
    #plt.text(MODE, 1.15, f" Mode: {MODE:.4f}")
    
    #plt.text(MEAN, 0.9, f" Mean: {MEAN:.4f}")
    #plt.text(MEAN-STD, 0.9, f" Mean-Std: {MEAN-STD:.4f}")
    #plt.text(MEAN+STD, 0.9, f" Mean+Std: {MEAN+STD:.4f}")
    plt.scatter(MEAN, 1, color="red", marker="+", s=200, label=f"Mean: {MEAN:.4f}")
    plt.scatter(MEAN-STD, 1, color="green", marker="X", s=200, label=f"Mean-Std: {MEAN-STD:.4f}")
    plt.scatter(MEAN+STD, 1, color="blue", marker="*", s=200, label=f"Mean+Std:  {MEAN+STD:.4f}")
    plt.xlabel(LABEL)
    plt.ylabel("Data")
    plt.title(f"Boxplot of {LABEL}")
    plt.legend()
    plt.grid()
    plt.show()
# -----------------------------------------------    
def HISTOGRAM_BOXPLOT_PLOTLY( DATA, XLABEL='X', TITLE='A', COLOR='cyan'):
    # Plotting histogram and boxplot
    import plotly.express as px
    fig = px.histogram(x=DATA, marginal="box", color_discrete_sequence=[COLOR])
    fig.update_layout(title=TITLE, xaxis_title=XLABEL, yaxis_title="Frequency")
    fig.show()     
# -----------------------------------------------
def PLOT_TIME_HIS(x, xlabel, y1, y1label, y2, y2label, y3, y3label, y4, y4label, Z, LOGX, LOGY):
    ## PLOT THE DATA
    import numpy as np
    import matplotlib.pyplot as plt
    # Define colors for each dataset
    colors = ['b', 'g', 'r', 'c']

    # Create subplots based on the value of Z
    fig, axs = plt.subplots(Z, 1, figsize=(14, 14))

    # Plot each dataset with a different color
    for i, y_data in enumerate([y1, y2, y3, y4][:Z]):
        axs[i].plot(x, y_data, color=colors[i])
        axs[i].set_title(f"{[y1label, y2label, y3label, y4label][i]} - MAX ABS: {np.max(np.abs(y_data)):.6e}")
        axs[i].set_xlabel(xlabel)
        #axs[i].set_ylabel()
        axs[i].grid()
        if LOGX == 1:
            axs[i].semilogx()
        if LOGY == 1:
            axs[i].semilogy()    

    # Adjust layout
    plt.tight_layout()
    plt.show()  
# -----------------------------------------------    
def MAXABS_FUN(DATA_FILE, COLUMN, I, J, Z):
    import numpy as np
    # Read and process displacement data
    if Z == 1:
        NameFiles = DATA_FILE
        filename = f"{NameFiles}_{I}.txt"
        D = np.loadtxt(filename)
        #print(D)
        MAXABS = np.max(np.abs([D[:, COLUMN]]))
    if Z == 2:
        NameFiles = DATA_FILE
        filename = f"{NameFiles}_{I}_{J}.txt"
        D = np.loadtxt(filename)
        #print(D)
        MAXABS = np.max(np.abs([D[:, COLUMN]]))    
    #print("MAX. ABS. :", MAXABS)
    return MAXABS
# -----------------------------------------------
def PLOT_2D(X, Y, Xfit, Yfit,X2, Y2, XLABEL, YLABEL, TITLE, COLOR, Z):
    import matplotlib.pyplot as plt
    #plt.figure(figsize=(12, 8))
    if Z == 1:
        # Plot 1 line
        plt.plot(X, Y,color=COLOR)
        plt.xlabel(XLABEL)
        plt.ylabel(YLABEL)
        plt.title(TITLE)
        plt.grid(True)
        plt.show()
    if Z == 2:
        plt.plot(X, Y, Xfit, Yfit, 'r--', linewidth=3)
        plt.title(TITLE)
        plt.xlabel(XLABEL)
        plt.ylabel(YLABEL)
        plt.legend(['curve', 'bilinear fitted'], loc='lower right')
        plt.grid(True)
        plt.show()
    if Z == 3:
        plt.plot(X, Y, Xfit, Yfit, 'r--', X2, Y2, 'green', linewidth=3)
        plt.title(TITLE)
        plt.xlabel(XLABEL)
        plt.ylabel(YLABEL)
        plt.legend(['curve', 'bilinear fitted','Dyn.'], loc='lower right')
        plt.grid(True)
        plt.show()     
        
# -----------------------------------------------
def OUTPUT_SECOND_COLUMN(FOLDER, X, COLUMN, I, Z):
    import numpy as np
    # Time History
    if Z == 1:
        filename = f"C:\\OPENSEESPY_SALAR\\{FOLDER}\\{X}.txt"
        data_collected = np.loadtxt(filename)
        X = data_collected[:, COLUMN]
    if Z == 2:
        filename = f"C:\\OPENSEESPY_SALAR\\{FOLDER}\\{X}_{I}.txt"
        data_collected = np.loadtxt(filename)
        X = data_collected[:, COLUMN]    
    return X 
# -----------------------------------------------
def BILNEAR_CURVE(Cur, Mom, SLOPE_NODE):
    import numpy as np
    # bilinear fitting
    SIZE = len(Mom)
    hh = np.zeros(SIZE-1)
    Aa = np.zeros(SIZE-1)
    for i in range(SIZE-1):
        hh[i] = Cur[i+1] - Cur[i]
        Aa[i] = (Mom[i] + Mom[i+1]) * 0.5 * hh[i]

    Area = sum(Aa)
    k0 = Mom[SLOPE_NODE] / Cur[SLOPE_NODE]
    fiy = (Mom[i+1] * max(Cur) * 0.5 - Area) / (Mom[i+1] * 0.5 - k0 * max(Cur) * 0.5)
    My = k0 * fiy
    X = np.array([0, fiy, max(Cur)])
    Y = np.array([0, My, Mom[i+1]])
    
    # EI and Ductility_Rito
    Elastic_ST = Y[1] / X[1]
    Plastic_ST = Y[2] / X[2]
    Tangent_ST = (Y[2] - Y[1]) / (X[2] - X[1])
    Ductility_Rito = X[2] / X[1]
    Over_Strength_Factor = Y[2] / Y[1]
    """
    # MOMENT-CURVAVTURE ANALYSIS
    print('+==========================+')
    print('=   Analysis curve fitted =')
    print('  Curvature    Moment')
    print('----------------------------')
    print(np.column_stack((X.T, Y.T)))
    print('+==========================+')
    print('+--------------------------------------------------------------------+')
    print(f' Elastic Flextural Rigidity :             {Elastic_EI:.2f}')
    print(f' Plastic Flextural Rigidity :             {Plastic_EI:.2f}')
    print(f' Tangent Flextural Rigidity :             {Tangent_EI:.2f}')
    print(f' Section Ductility Ratio :                {Ductility_Rito:.2f}')
    print(f' Section Over Stregth Factor:             {Over_Stregth_Factor:.2f}')
    print('+--------------------------------------------------------------------+')
    """
    """
    # PUSHOVER ANALYSIS
    print('+==========================+')
    print('=   Analysis curve fitted =')
    print('     Disp       Baser Shear')
    print('----------------------------')
    print(np.column_stack((X.T, Y.T)))
    print('+==========================+')
    print('+----------------------------------------------------+')
    print(f' Structure Elastic Stiffness :     {Elastic_ST:.2f}')
    print(f' Structure Plastic Stiffness :     {Plastic_ST:.2f}')
    print(f' Structure Tangent Stiffness :     {Tangent_ST:.2f}')
    print(f' Structure Ductility Ratio :       {Ductility_Rito:.2f}')
    print(f' Structure Over Strength Factor:   {Over_Strength_Factor:.2f}')
    print('+----------------------------------------------------+')
    """
    return X, Y, Elastic_ST, Plastic_ST, Tangent_ST, Ductility_Rito, Over_Strength_Factor
# -----------------------------------------------
def PLOT_2D(X, Y, Xfit, Yfit, X2, Y2, XLABEL, YLABEL, TITLE, LEGEND01, LEGEND02, LEGEND03, COLOR, Z):
    import matplotlib.pyplot as plt
    #plt.figure(figsize=(12, 8))
    if Z == 1:
        # Plot 1 line
        plt.plot(X, Y,color=COLOR)
        plt.xlabel(XLABEL)
        plt.ylabel(YLABEL)
        plt.title(TITLE)
        plt.grid(True)
        plt.show()
    if Z == 2:
        # Plot 2 lines
        plt.plot(X, Y, Xfit, Yfit, 'r--', linewidth=3)
        plt.title(TITLE)
        plt.xlabel(XLABEL)
        plt.ylabel(YLABEL)
        plt.legend([LEGEND01, LEGEND02], loc='lower right')
        plt.grid(True)
        plt.show()
    if Z == 3:
        # Plot 3 lines
        plt.plot(X, Y, Xfit, Yfit, 'r--', X2, Y2, 'g-*', linewidth=3)
        plt.title(TITLE)
        plt.xlabel(XLABEL)
        plt.ylabel(YLABEL)
        plt.legend([LEGEND01, LEGEND02, LEGEND03], loc='lower right')
        plt.grid(True)
        plt.show() 
# -----------------------------------------------
def PLOT3D(X, Y, Z, XLABEL, YLABEL, ZLABEL, TITLE):
    import plotly.graph_objects as go
    # Create a 3D scatter plot
    fig = go.Figure(data=[go.Scatter3d(x=X, y=Y, z=Z, mode='markers', marker=dict(size=5, color=Z))])
    fig.update_layout(scene=dict(xaxis_title=XLABEL, yaxis_title=YLABEL, zaxis_title=ZLABEL), title=TITLE)
    fig.show()
# -----------------------------------------------     
# Create a scatter plot
def PLOT_SCATTER(X, Y , XLABEL, YLABEL, TITLE, COLOR, LOG, ORDER):
    import matplotlib.pyplot as plt
    # Calculate linear regression parameters
    import numpy as np
    coefficients = np.polyfit(X, Y, ORDER)
    if ORDER == 1:
        a, b = coefficients
    if ORDER == 2:
        a, b, c = coefficients    
    if ORDER == 3:
        a, b, c, d = coefficients   
    if ORDER == 4:
        a, b, c, d, e = coefficients  
    if ORDER == 5:
        a, b, c, d, e, f = coefficients  
    if ORDER == 6:
        a, b, c, d, e, f, I = coefficients   
    if ORDER == 7:
        a, b, c, d, e, f, I, J = coefficients     
    y = [];yy = [];
    for i in range(len(X)):
        if ORDER == 1:
            y.append(a * X[i] + b)
        if ORDER == 2:
            y.append(a * X[i]**2 + b * X[i] + c)
        if ORDER == 3:
            y.append(a * X[i]**3 + b * X[i]**2 + c * X[i] + d)    
        if ORDER == 4:
            y.append(a * X[i]**4 + b * X[i]**3 + c * X[i]**2 + d * X[i] + e)  
        if ORDER == 5:
            y.append(a * X[i]**5 + b * X[i]**4 + c * X[i]**3 + d * X[i]**2 + e * X[i] + f)    
        if ORDER == 6:
            y.append(a * X[i]**6 + b * X[i]**5 + c * X[i]**4 + d * X[i]**3 + e * X[i]**2 + f * X[i] + I)     
        if ORDER == 7:
            y.append(a * X[i]**7 + b * X[i]**6 + c * X[i]**5 + d * X[i]**4 + e * X[i]**3 + f * X[i]**2 + I * X[i] + J)     
        yy.append(Y[i] - y[-1])
    y = np.array(y)    
    yy = np.array(yy) 
    # Calculate TSS
    Y_mean = np.mean(Y)
    TSS = np.sum((Y - Y_mean) ** 2)
    # Calculate RSS
    RSS = np.sum(yy ** 2)
    # Calculate R-squared
    R_squared = 1 - (RSS / TSS)
    #print(f"R-squared value: {R_squared:.4f}")
    plt.figure(figsize=(10,6))
    plt.scatter(X, Y, color=COLOR, marker='o', label='Data')
    # Add labels and title
    plt.xlabel(XLABEL)
    plt.ylabel(YLABEL)
    # Add the linear regression line
    if ORDER == 1:
        plt.plot(X, y, color='black', label=f'y = {a:.2f}x + {b:.2f} - R^2 = {R_squared:.3f}')
    if ORDER == 2:
        plt.plot(X, y, color='black', label=f'y = {a:.2f}x^2 + {b:.2f}x + {c:.2f} - R^2 = {R_squared:.3f}')
    if ORDER == 3:
        plt.plot(X, y, color='black', label=f'y = {a:.2f}x^3 + {b:.2f}x^2 + {c:.2f}x + {d:.2f} - R^2 = {R_squared:.3f}')  
    if ORDER == 4:
        plt.plot(X, y, color='black', label=f'y = {a:.2f}x^4 + {b:.2f}x^3 + {c:.2f}x^2 + {d:.2f}x + {e:.2f} - R^2 = {R_squared:.3f}') 
    if ORDER == 5:
        plt.plot(X, y, color='black', label=f'y = {a:.2f}x^5 + {b:.2f}x^4 + {c:.2f}x^3 + {d:.2f}x^2 + {e:.2f}x + {f:.2f} - R^2 = {R_squared:.3f}')  
    if ORDER == 6:
        plt.plot(X, y, color='black', label=f'y = {a:.2f}x^6 + {b:.2f}x^5 + {c:.2f}x^4 + {d:.2f}x^3 + {e:.2f}x^2 + {f:.2f}x + {I:.2f} - R^2 = {R_squared:.3f}')  
    if ORDER == 7:
        plt.plot(X, y, color='black', label=f'y = {a:.2f}x^7 + {b:.2f}x^6 + {c:.2f}x^5 + {d:.2f}x^4 + {e:.2f}x^3 + {f:.2f}x^2 + {I:.2f}x + {J:.2f} - R^2 = {R_squared:.3f}')               
    
    plt.title(TITLE)
    plt.grid(True)
    plt.legend()
    if LOG == 1:
        plt.semilogx();plt.semilogy();
    plt.show()

# -----------------------------------------------
def PLOT_SCATTER_PLOTLY(X, Y, XLABEL, YLABEL, TITLE, COLOR, LOG, ORDER):
    import plotly.graph_objects as go
    import numpy as np
    # Calculate linear regression parameters
    coefficients = np.polyfit(X, Y, ORDER)
    y = np.polyval(coefficients, X)
    
    # Calculate residuals
    residuals = Y - y
    
    # Calculate TSS
    Y_mean = np.mean(Y)
    TSS = np.sum((Y - Y_mean) ** 2)
    
    # Calculate RSS
    RSS = np.sum(residuals ** 2)
    
    # Calculate R-squared
    R_squared = 1 - (RSS / TSS)
    
    # Create scatter plot
    fig = go.Figure()
    fig.add_trace(go.Scatter(x=X, y=Y, mode='markers', marker=dict(color=COLOR), name='Data'))
    
    # Add the regression line
    fig.add_trace(go.Scatter(x=X, y=y, mode='lines', line=dict(color='black'),
                             name=f'Fit: R^2 = {R_squared:.3f}'))
    
    # Add labels and title
    fig.update_layout(
        title=TITLE,
        xaxis_title=XLABEL,
        yaxis_title=YLABEL,
        showlegend=True
    )
    
    # Set log scale if needed
    if LOG == 1:
        fig.update_xaxes(type="log")
        fig.update_yaxes(type="log")
    
    fig.show() 
# -----------------------------------------------
def plot_scatter_plotly(X, Y, XLABEL, YLABEL, TITLE, COLOR):
    import plotly.express as px
    fig = px.scatter(x=X, y=Y, color_discrete_sequence=[COLOR], labels={XLABEL: XLABEL, YLABEL: YLABEL})
    fig.update_layout(title=TITLE, xaxis_type='log', yaxis_type='log')
    fig.show() 
# ----------------------------------------------- 
def PLOT_HEATMAP(df):
    import plotly.figure_factory as ff
    # Calculate the correlation matrix
    corr_matrix = df.corr()

    # Create a correlation heatmap
    fig = ff.create_annotated_heatmap(
        z=corr_matrix.values,
        x=list(corr_matrix.columns),
        y=list(corr_matrix.index),
        annotation_text=corr_matrix.round(5).values,
        showscale=True,
        colorscale='Viridis'
    )

    # Update layout
    fig.update_layout(
        title='Correlation Heatmap',
        xaxis=dict(title='Variable'),
        yaxis=dict(title='Variable'),
        width=1200, height=1200
    )

    fig.show()
    
# -----------------------------------------------     
"""
Long short-term memory (LSTM) is a type
of recurrent neural network (RNN) aimed
at dealing with the vanishing gradient
problem present in traditional RNNs
"""
def PREDICT_LSTM(x, y, look_back, ITERATION):
    import numpy as np
    from keras.models import Sequential
    from keras.layers import LSTM, Dense
    # Prepare data for LSTM
    trainX, trainY = [], []
    for i in range(len(x) - look_back):
        trainX.append(x[i:i + look_back])
        trainY.append(y[i + look_back])

    trainX, trainY = np.array(trainX), np.array(trainY)

    # Build the LSTM model
    model = Sequential()
    model.add(LSTM(4, input_shape=(look_back, 1)))
    model.add(Dense(1))
    model.compile(loss='mean_squared_error', optimizer='adam')
    model.fit(trainX, trainY, epochs= ITERATION, batch_size=1, verbose=2)

    # Predict the next 'y' value
    next_x = np.array(x[-look_back:]).reshape(1, look_back, 1)
    predicted_y = model.predict(next_x)
    return predicted_y 

# -----------------------------------------------    
def Normal_CDF_Newton_Raphson(P_f, EPS=1e-3, tol=1e-6, max_iter=1000000):
    from scipy.stats import norm
    x = 0.0  # Initial guess (you can choose any value)
    
    for i in range(max_iter):
        xmin = x - EPS
        xmax = x + EPS
        f = norm.cdf(-x) - P_f
        fmin = norm.cdf(-xmin) - P_f
        fmax = norm.cdf(-xmax) - P_f
        df = (fmax - fmin) / (2 * EPS)
        dx = f / df
        f_prime_x = -norm.pdf(-x)
        
        if abs(dx) < tol:
            break
        
        x -= dx
    
    return x
# ----------------------------------------------- 
def MIX_HISTOGRAM(x, y, BINS, X, Y, TITLE):
    plt.figure(figsize=(8, 6))
    plt.hist(x, bins=BINS, alpha=0.5, label=X, color='blue')
    plt.hist(y, bins=BINS, alpha=0.5, label=Y, color='red')
    plt.legend(loc='upper right')
    plt.xlabel("Samples")
    plt.ylabel("Frequency")
    plt.title(TITLE)
    plt.show()
# -----------------------------------------------     
def plot_multiple_lines(x, y_list, LABELS, XLABEL, YLABEL, TITLE):
    import matplotlib.pyplot as plt
    """
    Plots multiple lines on the same graph.

    Parameters:
    x (list): List of x values.
    y_list (list of lists): List containing lists of y values for each line.
    labels (list): List of labels for each line.
    """
    for y, label in zip(y_list, LABELS):
        plt.plot(x, y, label=label)
    
    plt.xlabel(XLABEL)
    plt.ylabel(YLABEL)
    plt.title(TITLE)
    plt.legend()
    plt.grid()
    plt.show()
# -----------------------------------------------         
def DUCTILITY_DAMAGE_INDEX(x, YIELD, ULTIMATE):
    DI = (x - YIELD) / (ULTIMATE - YIELD)
    return DI     
# -----------------------------------------------         
def STRENGTH_DAMAGE_INDEX(x, YIELD, ULTIMATE):
    DI = (x - YIELD) / (ULTIMATE - YIELD)
    return DI

### -------------------------
###  DEFINE AND PLOT SECTION
### -------------------------
def Composite_Bridge_Section_Plot(Section_Tag, nFibZ, nFibY, SideWalk_z, SideWalk_y, SideWalk_C, Deck_z,
                                 Deck_y, Box_z, Box_y, tf01, bf, tf02, tw, DA01, DA02, DA03, PLOT, OUTPUT, I):

    import openseespy.opensees as op
    import opsvis as opsv
    import numpy as np
    
    Mat_Tag01 = 1 # Confined Concrete Section Tag
    Mat_Tag02 = 2 # Steel Plate Section Tag
    Mat_Tag03 = 3 # Steel Rebar Section Tag

    
    fc = -35 # [N/mm^2] Nominal concrete compressive strength
    Ec = 4700 * np.sqrt(-fc) # [N/mm^2] Concrete Elastic Modulus (the term in sqr root needs to be in psi

    # confined concrete
    Kfc = 1.3;			# ratio of confined to unconfined concrete strength - COLUMN
    fc1C = Kfc*fc;		# CONFINED concrete (mander model), maximum stress - COLUMN
    KfcB = 1.1;			# ratio of confined to unconfined concrete strength - BEAM
    fc1CB = KfcB*fc;		# CONFINED concrete (mander model), maximum stress - BEAM

    eps1C = 2*fc1C/Ec;	# strain at maximum stress 
    fc2C = 0.2*fc1C;		# ultimate stress
    eps2C = 5*eps1C;		# strain at ultimate stress 
    # unconfined concrete
    fc1U = fc;			# UNCONFINED concrete (todeschini parabolic model), maximum stress
    eps1U = -0.0025;			# strain at maximum strength of unconfined concrete
    fc2U = 0.2*fc1U;		# ultimate stress
    eps2U = -0.012;			# strain at ultimate stress
    Lambda = 0.1;				# ratio between unloading slope at $eps2 and initial slope $Ec
    # tensile-strength properties
    ftC = -0.55*fc1C;		# tensile strength +tension
    ftU = -0.55*fc1U;		# tensile strength +tension
    Ets = ftU/0.002;		# tension softening stiffness
    # PLATE MATERIAL PROPERTIES:
    FyP = 360			# Steel rebar yield stress
    CyP = 0.0018			# Steel rebar yield strain
    EsP = FyP/CyP				# modulus of steel
    BsP = 0.01				# strain-hardening ratio 
    R0P = 18.0				# control the transition from elastic to plastic branches
    cR1P = 0.925				# control the transition from elastic to plastic branches
    cR2P = 0.15				# control the transition from elastic to plastic branches
    # REBAR MATERIAL PROPERTIES:
    Fy = 4000			# Steel rebar yield stress
    Cy = 0.02			# Steel rebar yield strain
    Es = Fy/Cy				# modulus of steel
    Bs = 0.01				# strain-hardening ratio 
    R0 = 18.0				# control the transition from elastic to plastic branches
    cR1 = 0.925				# control the transition from elastic to plastic branches
    cR2 = 0.15				# control the transition from elastic to plastic branches
    # COLUMN
    op.uniaxialMaterial('Concrete02', Mat_Tag01, fc1C, eps1C, fc2C, eps2C, Lambda, ftC, Ets) # build core concrete (confined)
    op.uniaxialMaterial('Steel02', Mat_Tag02, FyP, EsP, BsP, R0P,cR1P,cR2P) # build plate material
    op.uniaxialMaterial('Steel02', Mat_Tag03, Fy, Es, Bs, R0,cR1,cR2) # build reinforcement material
    


    #nFibZ = 5 # NUMBER OF FIBER SECTIONIN Z DIRECTION
    #nFibY = 10 # NUMBER OF FIBER SECTIONIN Y DIRECTION
    As01 = (np.pi * (0.5 * DA01)**2) # [mm^2] SideWalk Rebar Area
    As02 = (np.pi * (0.5 * DA02)**2) # [mm^2] Deck Rebar Area
    As03 = (np.pi * (0.5 * DA03)**2) # [mm^2] Box Rebar Area
    
    hw = H - tf01 - tf02# Top Web Plate Height Beam
    # SIDEWALK
    rey1 = SideWalk_y - cover
    rez1 = SideWalk_z - cover
    # DECK
    rey2 = Deck_y - cover
    rez2 = Deck_z - cover
    # BOX
    rey3 = Box_y - cover
    rez3 = Box_z - cover

    FIBER_SEC = [['section', 'Fiber', Section_Tag, '-GJ', 1.0e6],
                 # CONCRETE SECION SIDEWALK
                 ['patch', 'rect', Mat_Tag01, nFibY, nFibZ, SideWalk_y, -Deck_z+SideWalk_C, 0, -Deck_z-SideWalk_z],# Left Side Walk
                 ['patch', 'rect', Mat_Tag01, nFibY, nFibZ, SideWalk_y, Deck_z+SideWalk_z, 0, +Deck_z-SideWalk_C],# Right Side Walk
                 # CONCRETE SECION DECK
                 ['patch', 'rect', Mat_Tag01, nFibY, nFibZ, -Deck_y, -Deck_z, 0, +Deck_z],# Road Deck
                 ['patch', 'rect', Mat_Tag01, nFibY, nFibZ, -Deck_y, -Deck_z, 0, +Deck_z],# Road Deck
                 # CONCRETE SECION BOX
                 ['patch', 'rect', Mat_Tag01, nFibY, nFibZ, -Deck_y-Box_y, -Deck_z+Z1, -Deck_y, -Deck_z+Box_z+Z1],# Road Deck Box Right 01
                 ['patch', 'rect', Mat_Tag01, nFibY, nFibZ, -Deck_y-Box_y, -Deck_z+Box_z+Z1+Z2, -Deck_y, -Deck_z+Box_z+(2*Z1+Z2)],# Road Deck Box Right 02
                 ['patch', 'rect', Mat_Tag01, nFibY, nFibZ, -Deck_y-Box_y, -Box_z*0.5, -Deck_y, Box_z*0.5],# Road Deck Box Center
                 ['patch', 'rect', Mat_Tag01, nFibY, nFibZ, -Deck_y-Box_y, +Deck_z-Box_z-Z1, -Deck_y, +Deck_z-Z1],# Road Deck Box Left 01
                 ['patch', 'rect', Mat_Tag01, nFibY, nFibZ, -Deck_y-Box_y, +Deck_z-Box_z-(2*Z1+Z2), -Deck_y, +Deck_z-Box_z-(Z1+Z2)],# Road Deck Box Left 02
                 # STEEL TOP FLANGE PLATE
                 ['patch', 'rect', Mat_Tag02, nFibY, nFibZ, -Deck_y-Box_y-tf01, -Deck_z+Z1, -Deck_y-Box_y, -Deck_z+Box_z+Z1],# Road Deck Top Flange Right 01
                 ['patch', 'rect', Mat_Tag02, nFibY, nFibZ, -Deck_y-Box_y-tf01, -Deck_z+Box_z+(Z1+Z2), -Deck_y-Box_y, -Deck_z+Box_z+(2*Z1+Z2)],# Road Deck Top Flange Right 02
                 ['patch', 'rect', Mat_Tag02, nFibY, nFibZ, -Deck_y-Box_y-tf01, -Box_z*0.5, -Deck_y-Box_y, Box_z*0.5],# Road Deck Top Flange Center
                 ['patch', 'rect', Mat_Tag02, nFibY, nFibZ, -Deck_y-Box_y-tf01, +Deck_z-Box_z-Z1, -Deck_y-Box_y, +Deck_z-Z1],# Road Deck Top Flange Left 01
                 ['patch', 'rect', Mat_Tag02, nFibY, nFibZ, -Deck_y-Box_y-tf01, +Deck_z-Box_z-(2*Z1+Z2), -Deck_y-Box_y, +Deck_z-Box_z-(Z1+Z2)],# Road Deck Top Flange Left 02
                 # STEEL BOTTOM FLANGE PLATE
                 ['patch', 'rect', Mat_Tag02, nFibY, nFibZ, -Deck_y-Box_y-tf01-hw-tf02, -Deck_z+Z1, -Deck_y-Box_y-tf01-hw, -Deck_z+Box_z+Z1],# Road Deck Top Flange Right 01
                 ['patch', 'rect', Mat_Tag02, nFibY, nFibZ, -Deck_y-Box_y-tf01-hw-tf02, -Deck_z+Box_z+(Z1+Z2), -Deck_y-Box_y-tf01-hw, -Deck_z+Box_z+(2*Z1+Z2)],# Road Deck Top Flange Right 02
                 ['patch', 'rect', Mat_Tag02, nFibY, nFibZ, -Deck_y-Box_y-tf01-hw-tf02, -Box_z*0.5, -Deck_y-Box_y-tf01-hw, Box_z*0.5],# Road Deck Top Flange Center
                 ['patch', 'rect', Mat_Tag02, nFibY, nFibZ, -Deck_y-Box_y-tf01-hw-tf02, +Deck_z-Box_z-Z1, -Deck_y-Box_y-tf01-hw, +Deck_z-Z1],# Road Deck Top Flange Left 01
                 ['patch', 'rect', Mat_Tag02, nFibY, nFibZ, -Deck_y-Box_y-tf01-hw-tf02, +Deck_z-Box_z-(2*Z1+Z2), -Deck_y-Box_y-tf01-hw, +Deck_z-Box_z-(Z1+Z2)],# Road Deck Top Flange Left 02
                 # STEEL WEB PLATE
                 ['patch', 'rect', Mat_Tag02, nFibY, nFibZ, -Deck_y-Box_y-tf01-hw, -Deck_z+0.5*Box_z+Z1-0.5*tw, -Deck_y-Box_y-tf01, -Deck_z+0.5*Box_z+Z1+0.5*tw],# Road Deck Web Right 01
                 ['patch', 'rect', Mat_Tag02, nFibY, nFibZ, -Deck_y-Box_y-tf01-hw, -Deck_z+0.5*Box_z+(2*Z1+Z2)-0.5*tw, -Deck_y-Box_y-tf01, -Deck_z+0.5*Box_z+(2*Z1+Z2)+0.5*tw],# Road Deck Web Right 02
                 ['patch', 'rect', Mat_Tag02, nFibY, nFibZ, -Deck_y-Box_y-tf01-hw, -Deck_z+0.5*Box_z+(3*Z1+2*Z2)-0.5*tw, -Deck_y-Box_y-tf01, -Deck_z+0.5*Box_z+(3*Z1+2*Z2)+0.5*tw],# Road Deck Web Right 03
                 ['patch', 'rect', Mat_Tag02, nFibY, nFibZ, -Deck_y-Box_y-tf01-hw, -Deck_z+0.5*Box_z+(4*Z2)-0.5*tw, -Deck_y-Box_y-tf01, -Deck_z+0.5*Box_z+(4*Z2)+0.5*tw],# Road Deck Web Right 04
                 ['patch', 'rect', Mat_Tag02, nFibY, nFibZ, -Deck_y-Box_y-tf01-hw, -Deck_z+0.5*Box_z+(Z1+5*Z2)-0.5*tw, -Deck_y-Box_y-tf01, -Deck_z+0.5*Box_z+(Z1+5*Z2)+0.5*tw],# Road Deck Web Right 05
                 # STEEL REBAR
                 ['layer', 'straight', Mat_Tag03, 10, As01, rey1, Deck_z+rez1, rey1, Deck_z-SideWalk_C+cover],# TOP REBAR LAYERS - SIDEWALK RIGHT
                 ['layer', 'straight', Mat_Tag03, 10, As01, cover, Deck_z+rez1, cover, Deck_z-SideWalk_C+cover],# BOTTOM REBAR LAYERS - SIDEWALK RIGHT
                 ['layer', 'straight', Mat_Tag03, 10, As01, rey1, -(Deck_z+rez1), rey1, -(Deck_z-SideWalk_C+cover)],# TOP REBAR LAYERS - SIDEWALK LEFT
                 ['layer', 'straight', Mat_Tag03, 10, As01,  cover, -(Deck_z+rez1),  cover, -(Deck_z-SideWalk_C+cover)],# BOTTOM REBAR LAYERS - SIDEWALK LEFT
                 ['layer', 'straight', Mat_Tag03, 65, As02, -rey2, -rez2, -rey2, rez2],# BOTTOM REBAR LAYERS - DECK
                 ['layer', 'straight', Mat_Tag03, 65, As02, -Deck_y*0.5, -rez2, -Deck_y*0.5, rez2],# MIDDLE REBAR LAYERS - DECK
                 ['layer', 'straight', Mat_Tag03, 65, As02, -cover, -rez2, -cover, rez2],# TOP REBAR LAYERS - DECK
                 ['layer', 'straight', Mat_Tag03,  3, As03, -(Deck_y+rey3), -Deck_z+Z1+cover, -(Deck_y+rey3), -Deck_z+Box_z+Z1-cover],# BOTTOM REBAR LAYERS - BOX 01
                 ['layer', 'straight', Mat_Tag03,  3, As03, -(Deck_y+cover), -Deck_z+Z1+cover, -(Deck_y+cover), -Deck_z+Box_z+Z1-cover],# TOP REBAR LAYERS - BOX 01
                 ['layer', 'straight', Mat_Tag03,  3, As03, -(Deck_y+rey3), -Deck_z+Box_z+Z1+Z2+cover, -(Deck_y+rey3), -Deck_z+Box_z+(2*Z1+Z2)-cover],# BOTTOM REBAR LAYERS - BOX 02
                 ['layer', 'straight', Mat_Tag03,  3, As03, -(Deck_y+cover), -Deck_z+Box_z+Z1+Z2+cover, -(Deck_y+cover), -Deck_z+Box_z+(2*Z1+Z2)-cover],# TOP REBAR LAYERS - BOX 02
                 ['layer', 'straight', Mat_Tag03,  3, As03, -(Deck_y+rey3), -Box_z*0.5+cover, -(Deck_y+rey3), Box_z*0.5-cover],# BOTTOM REBAR LAYERS - BOX 03 - MIDDLE
                 ['layer', 'straight', Mat_Tag03,  3, As03, -(Deck_y+cover), -Box_z*0.5+cover, -(Deck_y+cover), Box_z*0.5-cover],# TOP REBAR LAYERS - BOX 03 - MIDDLE
                 ['layer', 'straight', Mat_Tag03,  3, As03, -(Deck_y+rey3), Deck_z-Z1-cover, -(Deck_y+rey3), Deck_z-Box_z-Z1+cover],# BOTTOM REBAR LAYERS - BOX 05
                 ['layer', 'straight', Mat_Tag03,  3, As03, -(Deck_y+cover), Deck_z-Z1-cover, -(Deck_y+cover), Deck_z-Box_z-Z1+cover],# TOP REBAR LAYERS - BOX 05
                 ['layer', 'straight', Mat_Tag03,  3, As03, -(Deck_y+rey3), Deck_z-Box_z-Z1-Z2-cover, -(Deck_y+rey3), Deck_z-Box_z-(2*Z1+Z2)+cover],# BOTTOM REBAR LAYERS - BOX 04
                 ['layer', 'straight', Mat_Tag03,  3, As03, -(Deck_y+cover), Deck_z-Box_z-Z1-Z2-cover, -(Deck_y+cover), Deck_z-Box_z-(2*Z1+Z2)+cover],# TOP REBAR LAYERS - BOX 04

                ]

    if PLOT == 1:
        matcolor = ['gold', 'lightgrey']
        plt.figure(1)
        opsv.plot_fiber_section(FIBER_SEC, matcolor=matcolor)
        # Set the x and y limits
        plt.ylim(-1000, 1000)
        plt.xlim(-1500,-6850) # RIGHT
        plt.show()
        
        plt.figure(2)
        opsv.plot_fiber_section(FIBER_SEC, matcolor=matcolor)
        plt.ylim(-2500, 300)
        plt.xlim(-1500,-6850) #  RIGHT
        plt.show()

        plt.figure(3)
        opsv.plot_fiber_section(FIBER_SEC, matcolor=matcolor)
        plt.ylim(-1000, 1000)
        plt.xlim(600,-600) #  MIDDLE
        plt.show()

        plt.figure(4)
        opsv.plot_fiber_section(FIBER_SEC, matcolor=matcolor)
        plt.ylim(-2500, 300)
        plt.xlim(6850,1500) # LEFT
        plt.show()
        
        plt.figure(5)
        opsv.plot_fiber_section(FIBER_SEC, matcolor=matcolor)
        plt.ylim(-1000, 1000)
        plt.xlim(6850,1500) # LEFT
        plt.show()

        plt.figure(6)
        opsv.plot_fiber_section(FIBER_SEC, matcolor=matcolor)
        plt.axis('equal')
        plt.show()
        
    # CONCRETE FIBER
    op.recorder('Element','-ele', 50,'-file',f'{SALAR_DIR}{OUTPUT}_fiberCon_StressStrain_01_{I}.txt','section', 5,'fiber', SideWalk_y, +Deck_z-SideWalk_C+SideWalk_z,'stressStrain')# concrete fiber 01
    op.recorder('Element','-ele', 50,'-file',f'{SALAR_DIR}{OUTPUT}_fiberCon_StressStrain_02_{I}.txt','section', 5,'fiber', 0, +Deck_z,'stressStrain')# concrete fiber 02
    op.recorder('Element','-ele', 50,'-file',f'{SALAR_DIR}{OUTPUT}_fiberCon_StressStrain_03_{I}.txt','section', 5,'fiber', -Deck_y, +Deck_z,'stressStrain')# concrete fiber 03
    # STEEL REBAR FIBER
    op.recorder('Element','-ele', 50,'-file',f'{SALAR_DIR}{OUTPUT}_fiberReb_StressStrain_01_{I}.txt','section', 5,'fiber', rey1, Deck_z+rez1,'stressStrain')# steel rebar fiber 01 - TOP REBAR LAYERS - SIDEWALK RIGHT
    op.recorder('Element','-ele', 50,'-file',f'{SALAR_DIR}{OUTPUT}_fiberReb_StressStrain_02_{I}.txt','section', 5,'fiber', cover, Deck_z+rez1,'stressStrain')# steel rebar fiber 02 - BOTTOM REBAR LAYERS - SIDEWALK RIGHT
    op.recorder('Element','-ele', 50,'-file',f'{SALAR_DIR}{OUTPUT}_fiberReb_StressStrain_03_{I}.txt','section', 5,'fiber', -cover, -rez2,'stressStrain')# steel rebar fiber 03 - TOP REBAR LAYERS - DECK
    op.recorder('Element','-ele', 50,'-file',f'{SALAR_DIR}{OUTPUT}_fiberReb_StressStrain_04_{I}.txt','section', 5,'fiber', -Deck_y*0.5, -rez2,'stressStrain')# steel rebar fiber 04 - MIDDLE REBAR LAYERS - DECK
    op.recorder('Element','-ele', 50,'-file',f'{SALAR_DIR}{OUTPUT}_fiberReb_StressStrain_05_{I}.txt','section', 5,'fiber', -rey2, -rez2,'stressStrain')# steel rebar fiber 05 - BOTTOM REBAR LAYERS - DECK
    # STEEL PLATE FIBER
    op.recorder('Element','-ele', 50,'-file',f'{SALAR_DIR}{OUTPUT}_fiberPlate_StressStrain_01_{I}.txt','section', 5,'fiber', -Deck_y-Box_y, +Deck_z-Box_z-(2*Z1+Z2),'stressStrain')# steel plate fiber 01 - TOP PLATE LAYERS
    op.recorder('Element','-ele', 50,'-file',f'{SALAR_DIR}{OUTPUT}_fiberPlate_StressStrain_02_{I}.txt','section', 5,'fiber', -Deck_y-Box_y-tf01-hw-tf02, +Deck_z-Box_z-(2*Z1+Z2),'stressStrain')# steel plate fiber 02 - BOTTOM PLATE LAYERS        
    
    return FIBER_SEC

### -------------------------------
###    MOMENT-CURVATURE FUNCTION
### -------------------------------
import opsvis as opsv
def MC_ANALYSIS(P, DR, numIncr, TOLERANCE, ITERATION, J):
    import openseespy.opensees as op
    def MomentCurvature(ColSecTag, axialLoad, maxK, numIncr):

        # Define two nodes at (0,0)
        op.node(1, 0.0, 0.0)
        op.node(2, 0.0, 0.0)

        # Fix all degrees of freedom except axial and bending
        op.fix(1, 1, 1, 1)
        op.fix(2, 0, 1, 0)

        # Define element
        #                             tag ndI ndJ  secTag
        op.element('zeroLengthSection',  1,   1,   2,  ColSecTag)
        # Create recorder
        op.recorder('Node', '-file', f"{SALAR_DIR}CUR_{J}.txt",'-time', '-node', 2, '-dof', 3, 'disp')# Curvature Time History nodes 2
        op.recorder('Node', '-file', f"{SALAR_DIR}MOM_{J}.txt",'-time', '-node', 1, '-dof', 3, 'reaction')# Base Shear Time History nodes 1

        # Define constant axial load
        op.timeSeries('Constant', 1)
        op.pattern('Plain', 1, 1)
        op.load(2, axialLoad, 0.0, 0.0)

        # Define analysis parameters
        op.integrator('LoadControl', 0.0)
        op.system('SparseGeneral', '-piv')
        op.test('NormUnbalance', TOLERANCE, ITERATION)
        op.numberer('Plain')
        op.constraints('Plain')
        op.algorithm('Newton')
        op.analysis('Static')

        # Do one analysis for constant axial load
        op.analyze(1)

        # Define reference moment
        op.timeSeries('Linear', 2)
        op.pattern('Plain',2, 2)
        op.load(2, 0.0, 0.0, 1.0)

        # Compute curvature increment
        dK = maxK / numIncr

        # Use displacement control at node 2 for section analysis
        op.integrator('DisplacementControl', 2,3,dK,1,dK,dK)

        # Do the section analysis
        op.analyze(numIncr)


    op.wipe()
    
    ####      Start Moment Curvature Analysis
    # Define model builder
    # --------------------
    op.model('basic','-ndm',2,'-ndf',3)
    Section_Tag = 1 # Composite Section Tag
    nFibZ = 5 # NUMBER OF FIBER SECTIONIN Z DIRECTION
    nFibY = 25 # NUMBER OF FIBER SECTIONIN Y DIRECTION
    FS = Composite_Bridge_Section_Plot(Section_Tag, nFibZ, nFibY, SideWalk_z, SideWalk_y, SideWalk_C,
                                      Deck_z, Deck_y, Box_z, Box_y, tf01, bf, tf02, tw, DA01, DA02, DA03,
                                      PLOT=0, OUTPUT='MC', I=J)
    
    opsv.fib_sec_list_to_cmds(FS)
    
    H = SideWalk_y + Deck_y + Box_y + tf01 + tw + tf02 # I Section Height
    # -----------------------------------------------------------------------------------------------------
    # Yield Concrete Strain
    Cy = 0.004
    # Set Yield Curvature
    Ky = Cy / (0.5 * H)
    #print('Ky', Ky)

    # set ultimate Curvature
    Ku = Ky * DR
    #print('Ku', Ku)


    # Call the section analysis procedure:
    MomentCurvature(Section_Tag, P, Ku, numIncr)
    print(f'{J+1} MC Done.')
    op.wipe()

### -----------------------
###    PUSHOVER FUNCTION
### -----------------------
def PUSHOVER_ANALYSIS(Length, SideWalk_z, SideWalk_y, SideWalk_C, Deck_z, Deck_y,
                      Box_z, Box_y, tf01, bf, tf02, tw, Z1, Z2, cover,
                      H, DA01, DA02, DA03, WEIGHT, ND, NUM_NODES, DMAX, J):
    import openseespy.opensees as op
    op.wipe()
    op.model('basic', '-ndm', 2, '-ndf', 3)  # frame 2D

    # DEFINE BRIDGE COMPOSITE SECTION
    Section_Tag = 1 # Composite Section Tag
    nFibZ = 5 # NUMBER OF FIBER SECTIONIN Z DIRECTION
    nFibY = 70 # NUMBER OF FIBER SECTIONIN Y DIRECTION
    FS = Composite_Bridge_Section_Plot(Section_Tag, nFibZ, nFibY, SideWalk_z, SideWalk_y, SideWalk_C,
                                      Deck_z, Deck_y, Box_z, Box_y, tf01, bf, tf02, tw, DA01, DA02, DA03,
                                      PLOT=0, OUTPUT='PUSH', I=J)
    opsv.fib_sec_list_to_cmds(FS)
    
    # nodal coordinates:
    LL = Length / (NUM_NODES-1) # Lnength of each Beam elements
    for i in range(0, NUM_NODES):
        op.node(i+1, LL*i, 0.0) # node#, X, Y
        #print(i+1, LL*i)
        
    # Constraints -- Boundary Conditions
    op.fix(1, 1, 1, 0) # node DX DY RZ
    op.fix(NUM_NODES, 1, 1, 0)
    
    op.geomTransf('Linear', 1)
    numIntgrPts = 5
    for i in range(0, NUM_NODES-1):
        op.element('nonlinearBeamColumn', i+1, i+1, i+2, numIntgrPts, Section_Tag, 1)
        #print(i+1, i+1, i+2)
        
    # OUTPUT DATA
    op.recorder('Node', '-file', f"{SALAR_DIR}DTH_PUSH_{J}.txt",'-time', '-node', ND, '-dof', 1,2,3, 'disp')# Displacement Time History Node 2
    op.recorder('Node', '-file', f"{SALAR_DIR}BTH_PUSH_01_{J}.txt",'-time', '-node', 1, '-dof', 1,2,3, 'reaction')# Base Shear Time History Node 1
    op.recorder('Node', '-file', f"{SALAR_DIR}BTH_PUSH_101_{J}.txt",'-time', '-node', NUM_NODES, '-dof', 1,2,3, 'reaction')# Base Shear Time History Node 101
    op.recorder('Element', '-file', f"{SALAR_DIR}DEF_PUSH_{J}.txt",'-time', '-ele', 50, 'section', 5, 'deformations')# Curvature Time History 50
    for i in range(0, NUM_NODES-1):
        op.recorder('Element', '-file', f"{SALAR_DIR}LOCALFORCE_PUSH_{i}_{J}.txt",'-time', '-ele', i+1,'localForce')# Local Force Time History for Each Element 
    
    #defining gravity loads
    op.timeSeries('Linear', 1)
    op.pattern('Plain', 1, 1)
    for i in range(1, NUM_NODES+1):
        op.load(i, 0.0, -WEIGHT, 0.0)
    print('Model Built')    

    Tol = 1e-8 # convergence tolerance for test
    Iter = 1000# convergence iteration for test
    NstepGravity = 10
    DGravity = 1 / NstepGravity
    op.integrator('LoadControl', DGravity) # determine the next time step for an analysis
    op.numberer('Plain') # renumber dof's to minimize band-width (optimization), if you want to
    op.system('BandGeneral') # how to store and solve the system of equations in the analysis
    op.constraints('Plain') # how it handles boundary conditions
    op.test('NormDispIncr', Tol, Iter) # determine if convergence has been achieved at the end of an iteration step
    op.algorithm('Newton') # use Newton's solution algorithm: updates tangent stiffness at every iteration
    op.analysis('Static') # define type of analysis static or transient
    op.analyze(NstepGravity) # apply gravity

    op.loadConst('-time', 0.0) #maintain constant gravity loads and reset time to zero
    Dincr = 0.001 * DMAX
    Vload = 1#Weight
    maxNumIter = 1000
    tol = 1e-8

    op.timeSeries('Linear', 2)
    op.pattern('Plain', 200, 2)
    op.load(ND, 0.0, Vload, 0.0)

    op.wipeAnalysis()
    op.constraints('Plain')
    op.numberer('Plain')
    op.system('BandGeneral')
    op.test('EnergyIncr', Tol, maxNumIter)
    op.algorithm('Newton')

    IDctrlNode = ND ## INCREMENTAL DISPLACEMENT NODE
    IDctrlDOF = 2 ## INCREMENTAL DISPLACEMENT NODE IN Y DIRECTION

    op.integrator('DisplacementControl', IDctrlNode, IDctrlDOF, Dincr)
    op.analysis('Static')


    Nsteps =  int(DMAX/ Dincr)

    ok = op.analyze(Nsteps)
    #print(ok)


    # for gravity analysis, load control is fine, 0.1 is the load factor increment (http://opensees.berkeley.edu/wiki/index.php/Load_Control)

    test = {1:'NormDispIncr', 2: 'RelativeEnergyIncr', 4: 'RelativeNormUnbalance',5: 'RelativeNormDispIncr', 6: 'NormUnbalance'}
    algorithm = {1:'KrylovNewton', 2: 'SecantNewton' , 4: 'RaphsonNewton',5: 'PeriodicNewton', 6: 'BFGS', 7: 'Broyden', 8: 'NewtonLineSearch'}

    for i in test:
        for j in algorithm:

            if ok != 0:
                if j < 4:
                    op.algorithm(algorithm[j], '-initial')

                else:
                    op.algorithm(algorithm[j])

                op.test(test[i], Tol, 1000)
                ok = op.analyze(Nsteps)                            
                #print(test[i], algorithm[j], ok)             
                if ok == 0:
                    break
            else:
                continue

    #u2 = op.nodeDisp(2, 1)
    #print("u2 = ", u2)
    print(f'{J+1} Pushover Done.')
    op.wipe()

### ----------------------
###    DYNAMIC FUNCTION
### ----------------------
def DYNAMIC_ANALYSIS(Length, SideWalk_z, SideWalk_y, SideWalk_C, Deck_z, Deck_y,
                      Box_z, Box_y, tf01, bf, tf02, tw, Z1, Z2, cover,
                      H, DA01, DA02, DA03, MASS, WEIGHT, ND, NUM_NODES, J, J_MAX, GMfact_MAX):
    import openseespy.opensees as op
    op.wipe()
    op.model('basic', '-ndm', 2, '-ndf', 3)  # frame 2D
    
    # DEFINE BRIDGE COMPOSITE SECTION
    Section_Tag = 1 # Composite Section Tag
    nFibZ = 5 # NUMBER OF FIBER SECTIONIN Z DIRECTION
    nFibY = 70 # NUMBER OF FIBER SECTIONIN Y DIRECTION
    FS = Composite_Bridge_Section_Plot(Section_Tag, nFibZ, nFibY, SideWalk_z, SideWalk_y, SideWalk_C,
                                      Deck_z, Deck_y, Box_z, Box_y, tf01, bf, tf02, tw, DA01, DA02, DA03,
                                      PLOT=0, OUTPUT='DYN', I=J)
    opsv.fib_sec_list_to_cmds(FS)
    
    # nodal coordinates:
    LL = Length / (NUM_NODES-1) # Lnength of each Beam elements
    for i in range(0, NUM_NODES):
        op.node(i+1, LL*i, 0.0) # node#, X, Y
        #print(i+1, LL*i)
        
    # Constraints -- Boundary Conditions
    op.fix(1, 1, 1, 0) # node DX DY RZ
    op.fix(NUM_NODES, 1, 1, 0)
    
    op.geomTransf('Linear', 1)
    numIntgrPts = 5
    for i in range(0, NUM_NODES-1):
        op.element('nonlinearBeamColumn', i+1, i+1, i+2, numIntgrPts, Section_Tag, 1)
        #print(i+1, i+1, i+2)

    # OUTPUT DATA
    op.recorder('EnvelopeNode','-file', f"{SALAR_DIR}MD_{J}.txt" ,'-time','-node',ND,'-dof',2,'disp');# max. displacements of free node ND
    op.recorder('EnvelopeNode','-file',f"{SALAR_DIR}MV_{J}.txt" ,'-time','-node',ND,'-dof',2,'vel');# max. vel of free node ND
    op.recorder('EnvelopeNode','-file', f"{SALAR_DIR}MA_{J}.txt" ,'-time','-node',ND,'-dof',2,'accel');# max. accel of free node ND	
    op.recorder('Node', '-file', f"{SALAR_DIR}DTH_DYN_{J}.txt",'-time', '-node', ND, '-dof', 1,2,3, 'disp')# Displacement Time History Node ND
    op.recorder('Node', '-file', f"{SALAR_DIR}VTH_DYN_{J}.txt",'-time', '-node', ND, '-dof', 1,2,3, 'vel')# Velocity Time History Node ND
    op.recorder('Node', '-file', f"{SALAR_DIR}ATH_DYN_{J}.txt",'-time', '-node', ND, '-dof', 1,2,3, 'accel')# Acceleration Time History Node ND
    op.recorder('Node', '-file', f"{SALAR_DIR}BTH_DYN_01_{J}.txt",'-time', '-node', 1, '-dof', 1,2,3, 'reaction')# Base Shear Time History Node 1
    op.recorder('Node', '-file', f"{SALAR_DIR}BTH_DYN_101_{J}.txt",'-time', '-node', NUM_NODES, '-dof', 1,2,3, 'reaction')# Base Shear Time History Node 101
    op.recorder('Element', '-file', f"{SALAR_DIR}DEF_DYN_{J}.txt",'-time', '-ele', 50, 'section', 5, 'deformations')# Curvature Time History 50
    for i in range(0, NUM_NODES-1):
        op.recorder('Element', '-file', f"{SALAR_DIR}LOCALFORCE_DYN_{i}_{J}.txt",'-time', '-ele', i+1,'localForce')# Local Force Time History for Each Element 
    
    #defining gravity loads
    op.timeSeries('Linear', 1)
    op.pattern('Plain', 1, 1)
    # Define Weight
    for j in range(1, NUM_NODES+1): 
        op.load(j, 0.0, -WEIGHT, 0.0)
        
    # Define Mass
    for j in range(1, NUM_NODES+1): 
        op.mass(j, 0.0, MASS, 0.0)    
    print('Model Built')    

    Tol = 1e-8 # convergence tolerance for test
    Iter = 1000# convergence iteration for test                     # 6
    NstepGravity = 10
    DGravity = 1/NstepGravity
    op.integrator('LoadControl', DGravity) # determine the next time step for an analysis
    op.numberer('Plain') # renumber dof's to minimize band-width (optimization), if you want to
    op.system('BandGeneral') # how to store and solve the system of equations in the analysis
    op.constraints('Plain') # how it handles boundary conditions
    op.test('NormDispIncr', Tol, Iter) # determine if convergence has been achieved at the end of an iteration step
    op.algorithm('Newton') # use Newton's solution algorithm: updates tangent stiffness at every iteration
    op.analysis('Static') # define type of analysis static or transient
    op.analyze(NstepGravity) # apply gravity

    op.loadConst('-time', 0.0) #maintain constant gravity loads and reset time to zero

    #applying Dynamic Ground motion analysis
    GMdirection = 2 # 1: x-axis direction 2: y-axis direction
    GMfile = 'BM68elc.acc'
    """
    A = []
    for ii in range(1, 3):
        Lambda01 = op.eigen('-fullGenLapack', ii) # eigenvalue mode 1
        Lambda02 = op.eigen('-genBandArpack', ii) # eigenvalue mode 1
        omega = math.pow(max(min(Lambda01), min(Lambda02)), 0.5)
        A.append(omega)
        
    Omega = max(A)
    """
    Lambda01 = op.eigen('-fullGenLapack', 1) # eigenvalue mode 1
    Lambda02 = op.eigen('-genBandArpack', 1) # eigenvalue mode 1
    Omega = np.power(max(min(Lambda01), min(Lambda02)), 0.5)
    
    betaKcomm = 2 * (0.02/Omega)

    xDamp = 0.02				# 2% damping ratio
    alphaM = 0.0				# M-prop. damping; D = alphaM*M	
    betaKcurr = 0.0		# K-proportional damping;      +beatKcurr*KCurrent
    betaKinit = 0.0 # initial-stiffness proportional damping      +beatKinit*Kini

    op.rayleigh(alphaM,betaKcurr, betaKinit, betaKcomm) # RAYLEIGH damping

    # Uniform EXCITATION: acceleration input
    IDloadTag = 400			# load tag
    dt = 0.01			# time step for input ground motion
    GMfact = ((J+1) / J_MAX) * GMfact_MAX	 # INCREASE THE ACCELERATION FACTOR: data in input file is in g Unifts -- ACCELERATION TH
    maxNumIter = 1000
    op.timeSeries('Path', 2, '-dt', dt, '-filePath', GMfile, '-factor', GMfact)
    op.pattern('UniformExcitation', IDloadTag, GMdirection, '-accel', 2) 

    op.wipeAnalysis()
    op.constraints('Transformation')
    op.numberer('Plain')
    op.system('BandGeneral')
    op.test('RelativeNormUnbalance', Tol, maxNumIter)
    op.algorithm('RaphsonNewton')

    NewmarkGamma = 0.5
    NewmarkBeta = 0.25
    op.integrator('Newmark', NewmarkGamma, NewmarkBeta)
    op.analysis('Transient')

    DtAnalysis = 0.01
    TmaxAnalysis = 10.0

    Nsteps =  int(TmaxAnalysis/ DtAnalysis)

    ok = op.analyze(Nsteps, DtAnalysis)

    tCurrent = op.getTime()

    # for gravity analysis, load control is fine, 0.1 is the load factor increment (http://opensees.berkeley.edu/wiki/index.php/Load_Control)
    #test = {1:'NormDispIncr', 2: 'RelativeEnergyIncr', 3:'EnergyIncr', 4: 'RelativeNormUnbalance',5: 'RelativeNormDispIncr', 6: 'NormUnbalance'}
    #algorithm = {1:'KrylovNewton', 2: 'SecantNewton' , 3:'ModifiedNewton' , 4: 'RaphsonNewton',5: 'PeriodicNewton', 6: 'BFGS', 7: 'Broyden', 8: 'NewtonLineSearch'}
    
    test = {1:'NormDispIncr', 2: 'RelativeEnergyIncr', 4: 'EnergyIncr',5: 'RelativeNormDispIncr', 6: 'NormUnbalance'}
    algorithm = {1:'KrylovNewton', 2: 'SecantNewton' , 4: 'ModifiedNewton',5: 'PeriodicNewton', 6: 'BFGS', 7: 'Broyden', 8: 'NewtonLineSearch'}

    for i in test:
        for j in algorithm:

            if ok != 0:
                if j < 4:
                    op.algorithm(algorithm[j], '-initial')

                else:
                    op.algorithm(algorithm[j])

                op.test(test[i], Tol, 1000)
                ok = op.analyze(Nsteps, DtAnalysis)                            
                print(test[i], algorithm[j], ok)             
                if ok == 0:
                    break
            else:
                continue

    #u2 = op.nodeDisp(ND01, 1)
    #print("u2 = ", u2)
    print(f'{J+1} Dynamic Done.')
    op.wipe()
    T = (2*np.pi)/Omega # Structural Period
    #print(T)
    return T

# COMPOSITE BRIDGE SECTION
Length = 30000 # [mm] Bridge Length
SideWalk_z = 1000 # [mm] SideWalk Width
SideWalk_y = 150 # [mm] SideWalk Height
SideWalk_C = 250 # [mm] SideWalk to deck Connection
Deck_z = 11500/2 # [mm] Bridge Deck Width Concrete Top Flange
Deck_y = 300 # [mm] Bridge Thickness Concrete Top Flange
Box_z = 500 # [mm] Width Concrete Box Under Deck
Box_y = 200 # [mm] Thickness Concrete Box Under Deck
tf01 = 30 # [mm] Top Flange Plate Thickness Beam
bf = Box_z # [mm] Top Flange Plate Thickness Beam (BOX WIDTH, TOP AND BOTTTOM PLATE WIDTH IS THE SAME AN EQUAL)
tf02 = 30 # [mm] Bottom Flange Plate Thickness Beam

tw = 16 # [mm] Top Web Plate Thickness Beam 01

Z1 = 500 # [mm]
Z2 = 2000 # [mm]
cover = 50  # [mm] Concrete Cover
H = 1800 # [mm] I Section Beam Height

DA01 = 30 # [mm] Rebar Diameter for Sidewalk
DA02 = 30 # [mm] Rebar Diameter for Deck
DA03 = 30 # [mm] Rebar Diameter for Box

Section_Tag = 0
nFibZ = 1
nFibY = 1
PLOT = 1
OUTPUT = 'PUSH'
I = 0
d = Composite_Bridge_Section_Plot(Section_Tag, nFibZ, nFibY, SideWalk_z, SideWalk_y, SideWalk_C, Deck_z,
                                 Deck_y, Box_z, Box_y, tf01, bf, tf02, tw, DA01, DA02, DA03, PLOT, OUTPUT, I)

<Figure size 640x480 with 0 Axes>

<Figure size 640x480 with 0 Axes>

<Figure size 640x480 with 0 Axes>

<Figure size 640x480 with 0 Axes>

<Figure size 640x480 with 0 Axes>

<Figure size 640x480 with 0 Axes>

############################# 2D PLOT

# Number of nodes
num_nodes = 101

# Generate node positions
x = [(i-1) * Length / (num_nodes - 1) for i in range(1, num_nodes+1)]
y = [0] * num_nodes  # All nodes are on the x-axis

def PLOTLY_2D_BEAM(x, y, num_nodes, TITLE):
    import plotly.graph_objects as go
    # Create the plot
    fig = go.Figure()

    # Add nodes to the plot
    fig.add_trace(go.Scatter(
        x=x, y=y,
        mode='markers+text',
        text=[f'Node {i}' for i in range(1, num_nodes+1)],
        textposition='top center',
        marker=dict(size=8, color='blue'),
        name='Nodes'
    ))

    # Add the beam line
    fig.add_trace(go.Scatter(
        x=[0, Length], y=[0, 0],
        mode='lines',
        line=dict(color='black', width=2),
        name='Beam'
    ))

    # Add triangular points at Node 1 and Node 101
    fig.add_trace(go.Scatter(
        x=[x[0], x[-1]], y=[y[0], y[-1]],
        mode='markers',
        marker=dict(size=12, symbol='triangle-up', color='red'),
        name='Simply Support Points'
    ))

    # Update layout for better visualization
    fig.update_layout(
        title=TITLE,
        xaxis_title='Length (mm)',
        yaxis_title='Position',
        showlegend=True
    )

    # Show the plot
    fig.show()

############################# 3D PLOT

# Generate node positions
x = [(i-1) * Length / (num_nodes - 1) for i in range(1, num_nodes+1)]
y = [0] * num_nodes  # All nodes are on the x-axis
z = [0] * num_nodes  # All nodes are on the x-axis

def PLOTLY_3D_BEAM(x, y, z, num_nodes, TITLE):
    import plotly.graph_objects as go
    # Create the plot
    fig = go.Figure()

    # Add nodes to the plot
    fig.add_trace(go.Scatter3d(
        x=x, y=y, z=z,
        mode='markers+text',
        text=[f'Node {i}' for i in range(1, num_nodes+1)],
        textposition='top center',
        marker=dict(size=8, color='blue'),
        name='Nodes'
    ))

    # Add the beam line
    fig.add_trace(go.Scatter3d(
        x=[0, Length], y=[0, 0], z=[0, 0],
        mode='lines',
        line=dict(color='black', width=2),
        name='Beam'
    ))

    # Add triangular points at Node 1 and Node 101
    fig.add_trace(go.Scatter3d(
        x=[x[0], x[-1]], y=[y[0], y[-1]], z=[z[0], z[-1]],
        mode='markers',
        marker=dict(size=20, color='red'),
        name='Simply Support Points'
    ))

    # Update layout for better visualization
    fig.update_layout(
        title=TITLE,
        scene=dict(
            xaxis_title='Length (mm)',
            yaxis_title='Position Y',
            zaxis_title='Position Z'
        ),
        showlegend=True
    )

    # Show the plot
    fig.show()
#--------------------------------
PLOTLY_2D_BEAM(x, y, num_nodes, TITLE='2D Simply Supported Beam with 101 Nodes and Triangular Points at Node 1 and Node 101')     
#PLOTLY_3D_BEAM(x, y, z, num_nodes, TITLE='3D Simply Supported Beam with 101 Nodes and Triangular Points at Node 1 and Node 101')

# RUN MOMENT-CURVATURE ANLYSIS
Axial_Force = 0.0 # [N]
DR = 66.5 # set ductility ratio for moment curvature
numIncr = 200# Number of analysis increments
TOLERANCE = 1e8 # Converganve tolerance for moment curvature
MAX_ITERATION = 1000000 # Maximum Tolerance for moment curvature
MC_ANALYSIS(Axial_Force, DR, numIncr, TOLERANCE, MAX_ITERATION, J=0)

1 MC Done.

CUR = OUTPUT_SECOND_COLUMN(FOLDER_NAME,'CUR', 1, 0, 2)
MOM = OUTPUT_SECOND_COLUMN(FOLDER_NAME,'MOM', 1, 0, 2)
xxc, yyc, _, _, _, _, _ = BILNEAR_CURVE(CUR, -MOM, 2)
xxc = np.abs(xxc); yyc = np.abs(yyc); # ABSOLUTE VALUE
XLABEL = 'Curvature'
YLABEL = 'Moment'
LEGEND01 = 'Curve'
LEGEND02 = 'Bilinear Fitted'
TITLE = 'Last data Moment and Curvature Analysis'
COLOR = 'black'
PLOT_2D(CUR, -MOM, xxc, yyc, _, _, XLABEL, YLABEL, TITLE, LEGEND01, LEGEND02, _, COLOR='black', Z=2) 
print(f'\t\t Ductility Ratio: {yyc[2]/yyc[1]:.4f}')

		 Ductility Ratio: 4.2472

### -----------------------------------------------------
###   Composite Bridge Superstructure Response Spectrum
### -----------------------------------------------------

g =  9810 # [mm/s^2] Acceleration due to Gravity
G_Factor_MAX = 2 # Amplified Factor due to Acceleration Gravity 

DMAX = -150 # [mm] Max. Pushover Incremental Displacement
ND = 50  # NODE NUMBER FOR INCREMENTAL DISPLACEMENT
NUM_NODES = 101 # NUMBER OF NODES IN BEAM ELEMENT
Kef = 433147.23743411334 # [N/mm] Structural Lateral Elastic Stiffness

DATA_FILE05 =f'C:\\OPENSEESPY_SALAR\\{FOLDER_NAME}\\T.txt' #STRUCTURE PERIOD

t = time.localtime()
current_time = time.strftime("%H:%M:%S", t)
print(f"Current time (HH:MM:SS): {current_time}\n\n")

NUM_ITERATION = 50
Tmax = 0.25 # Maximum Period 
Massef = Kef * (Tmax / (2*np.pi))**2
PCol = Massef / 101 # Mass of each Node (Truss has 62 Nodes)
PColw = PCol * g # Weight of each Node
print(f'MASS: {PCol:.5f} WEIGHT: {PColw:.5f}')
with open(DATA_FILE05, "w") as file:
    for i in range(NUM_ITERATION):
        PUSHOVER_ANALYSIS(Length, SideWalk_z, SideWalk_y, SideWalk_C, Deck_z, Deck_y,
                      Box_z, Box_y, tf01, bf, tf02, tw, Z1, Z2, cover,
                      H, DA01, DA02, DA03, PColw, ND, NUM_NODES, DMAX, i)
        a = DYNAMIC_ANALYSIS(Length, SideWalk_z, SideWalk_y, SideWalk_C, Deck_z, Deck_y,
                      Box_z, Box_y, tf01, bf, tf02, tw, Z1, Z2, cover,
                      H, DA01, DA02, DA03, PCol, PColw, ND, NUM_NODES, i, NUM_ITERATION, G_Factor_MAX)
        file.write(f"{i+1} {a:.4f} {((i+1) / NUM_ITERATION) * G_Factor_MAX}\n")
        print(f'Real Period: {a:.4f} - Period: {Tmax:.4f} - Factor: {((i+1) / NUM_ITERATION) * G_Factor_MAX}')
    
t = time.localtime()
current_time = time.strftime("%H:%M:%S", t)
print(f"Current time (HH:MM:SS): {current_time}\n\n")

Current time (HH:MM:SS): 21:01:17


1 MASS: 6.78945 WEIGHT: 66604.48324
Model Built
1 Pushover Done.
Model Built

WARNING: CTestRelativeNormUnbalance::test() - failed to converge 
after: 1000 iterations
AcceleratedNewton::solveCurrentStep() -The ConvergenceTest object failed in test()
DirectIntegrationAnalysis::analyze() - the Algorithm failed at time 0.03
OpenSees > analyze failed, returned: -3 error flag

NormDispIncr KrylovNewton 0
1 Dynamic Done.
Real Period: 0.2532 - Period: 0.2500 - Factor: 0.04
2 MASS: 6.78945 WEIGHT: 66604.48324
Model Built
2 Pushover Done.
Model Built

WARNING: CTestRelativeNormUnbalance::test() - failed to converge 
after: 1000 iterations
AcceleratedNewton::solveCurrentStep() -The ConvergenceTest object failed in test()
DirectIntegrationAnalysis::analyze() - the Algorithm failed at time 0.02
OpenSees > analyze failed, returned: -3 error flag

NormDispIncr KrylovNewton 0
2 Dynamic Done.
Real Period: 0.2532 - Period: 0.2500 - Factor: 0.08
3 MASS: 6.78945 WEIGHT: 66604.48324
Model Built
3 Pushover Done.
Model Built

WARNING: CTestRelativeNormUnbalance::test() - failed to converge 
after: 1000 iterations
AcceleratedNewton::solveCurrentStep() -The ConvergenceTest object failed in test()
DirectIntegrationAnalysis::analyze() - the Algorithm failed at time 0.02
OpenSees > analyze failed, returned: -3 error flag

NormDispIncr KrylovNewton 0
3 Dynamic Done.
Real Period: 0.2532 - Period: 0.2500 - Factor: 0.12
4 MASS: 6.78945 WEIGHT: 66604.48324
Model Built
4 Pushover Done.
Model Built

WARNING: CTestRelativeNormUnbalance::test() - failed to converge 
after: 1000 iterations
AcceleratedNewton::solveCurrentStep() -The ConvergenceTest object failed in test()
DirectIntegrationAnalysis::analyze() - the Algorithm failed at time 0.01
OpenSees > analyze failed, returned: -3 error flag

NormDispIncr KrylovNewton 0
4 Dynamic Done.
Real Period: 0.2532 - Period: 0.2500 - Factor: 0.16
5 MASS: 6.78945 WEIGHT: 66604.48324
Model Built
5 Pushover Done.
Model Built

WARNING: CTestRelativeNormUnbalance::test() - failed to converge 
after: 1000 iterations
AcceleratedNewton::solveCurrentStep() -The ConvergenceTest object failed in test()
DirectIntegrationAnalysis::analyze() - the Algorithm failed at time 0.01
OpenSees > analyze failed, returned: -3 error flag

# Evaluation for Last Data for Difference ‌Between Real Period and Simple Linear Analysis Period
print(f'Real Period: {a:.10f} - Period: {Tmax:.10f}')
print(a/Tmax - 1)
print(Kef * Tmax/a)

Real Period: 0.2531981493 - Period: 0.2500000000
0.012792597021864527
427676.14880656794

## FILE ADDRESS
DATA_FILE01 =f'C:\\OPENSEESPY_SALAR\\{FOLDER_NAME}\\MD'  # DISPLACEMENT TIME HISTORY
DATA_FILE02 =f'C:\\OPENSEESPY_SALAR\\{FOLDER_NAME}\\MV'  # VELOCITY TIME HISTORY
DATA_FILE03 =f'C:\\OPENSEESPY_SALAR\\{FOLDER_NAME}\\MA'  # ACCELERATION TIME HISTORY

DATA_FILE04 =f'C:\\OPENSEESPY_SALAR\\{FOLDER_NAME}\\PUSH_nodeDisplacements'  # NODE DISPLACEMENT - PUSH
DATA_FILE05 =f'C:\\OPENSEESPY_SALAR\\{FOLDER_NAME}\\PUSH_elementForces'  # ELEMENT FORCE - PUSH
DATA_FILE06 =f'C:\\OPENSEESPY_SALAR\\{FOLDER_NAME}\\PUSH_fiber_StressStrain'  # SECTION STRAIN-STRESS - PUSH

DATA_FILE07 =f'C:\\OPENSEESPY_SALAR\\{FOLDER_NAME}\\DYN_nodeDisplacements'  # NODE DISPLACEMENT - DYN
DATA_FILE08 =f'C:\\OPENSEESPY_SALAR\\{FOLDER_NAME}\\DYN_elementForces'  # ELEMENT FORCE - DYN
DATA_FILE09 =f'C:\\OPENSEESPY_SALAR\\{FOLDER_NAME}\\DYN_fiber_StressStrain'  # SECTION STRAIN-STRESS - DYN

DATA_FILE10 =f'C:\\OPENSEESPY_SALAR\\{FOLDER_NAME}\\DEF_PUSH'  # DEFORMATION TIME HISTORY - PUSH
DATA_FILE11 =f'C:\\OPENSEESPY_SALAR\\{FOLDER_NAME}\\DEF_DYN'  # DEFORMATION TIME HISTORY - DYN

### LOAD OUTPUT DATAS

import numpy as np
filename = f'C:\\OPENSEESPY_SALAR\\{FOLDER_NAME}\\T.txt'
data = np.loadtxt(filename)
T = data[:, 1] # Period
AF = data[:, 2] # Amplified Factor due to Acceleration Gravity 

pgd = [] # Peak Displacement 
pgv = [] # Peak Velocity
pga = [] # Peak Acceleration
pgb = [] # Base shear during dynamic
period = []
nf = [] # natural frequency

diS = [] # Structure Ductility Damage Index
diC = [] # Section Ductility Damage Index
momr = [] # Resistance Moment Capacity from Moment Curvature Analysis
moml = [] # Applied Moment from Dynamic Analysis
bDbP = [] # Ratio Base-shear Dynamic to Base-shear Pushover
dDdP = [] # Ratio Displacement Dynamic to Displacement Pushover

diASP01 = [] # Steel Plate Axial Ductility Damage Index 01
diASP02 = [] # Steel Plate Axial Ductility Damage Index 02

diAS01 = [] # Steel Rebar Axial Ductility Damage Index 01
diAS02 = [] # Steel Rebar Axial Ductility Damage Index 02
diAS03 = [] # Steel Rebar Axial Ductility Damage Index 03
diAS04 = [] # Steel Rebar Axial Ductility Damage Index 04
diAS05 = [] # Steel Rebar Axial Ductility Damage Index 05

diAC01 = [] # Concrete Axial Ductility Damage Index 01
diAC02 = [] # Concrete Axial Ductility Damage Index 02
diAC03 = [] # Concrete Axial Ductility Damage Index 03

Dyn_fiber_C_Strain01 = [] # Concrete Fiber Strain 01 - DYN
Dyn_fiber_C_Strain02 = [] # Concrete Fiber Strain 02 - DYN
Dyn_fiber_C_Strain03 = [] # Concrete Fiber Strain 03 - DYN
Dyn_fiber_C_Stress01 = [] # Concrete Fiber Stress 01 - DYN
Dyn_fiber_C_Stress02 = [] # Concrete Fiber Stress 02 - DYN
Dyn_fiber_C_Stress03 = [] # Concrete Fiber Stress 03 - DYN

Dyn_fiber_R_Strain01 = [] # Steel Rebar Fiber Strain 01 - DYN
Dyn_fiber_R_Strain02 = [] # Steel Rebar Fiber Strain 02 - DYN
Dyn_fiber_R_Strain03 = [] # Steel Rebar Fiber Strain 03 - DYN
Dyn_fiber_R_Strain04 = [] # Steel Rebar Fiber Strain 04 - DYN
Dyn_fiber_R_Strain05 = [] # Steel Rebar Fiber Strain 05 - DYN
Dyn_fiber_R_Stress01 = [] # Steel Rebar Fiber Stress 01 - DYN
Dyn_fiber_R_Stress02 = [] # Steel Rebar Fiber Stress 02 - DYN
Dyn_fiber_R_Stress03 = [] # Steel Rebar Fiber Stress 03 - DYN
Dyn_fiber_R_Stress04 = [] # Steel Rebar Fiber Stress 04 - DYN
Dyn_fiber_R_Stress05 = [] # Steel Rebar Fiber Stress 05 - DYN

Dyn_fiber_P_Strain01 = [] # Steel Plate Fiber Strain 01 - DYN
Dyn_fiber_P_Strain02 = [] # Steel Plate Fiber Strain 02 - DYN
Dyn_fiber_P_Stress01 = [] # Steel Plate Fiber Stress 01 - DYN
Dyn_fiber_P_Stress02 = [] # Steel Plate Fiber Stress 02 - DYN

cur = [] # Curvature of Node 50
osf = [] # Over Strength Factor of Structure
dr = []  # Ductility Ratio of Structure
eei = [] # Elastic Flexural rigidity of Structure
pei = [] # Plastic Flexural rigidity of Structure
yd = [] # Yield Displacement of Structure
yb = [] # Yield Base-sheaer of Structure
ud = [] # Utilamte Displacement of Structure
ub = [] # Utilamte Base-sheaer of Structure

DMAX = -150 # [mm] Max. Pushover Incremental Displacement

ysp_strain = 0.0018 # Yield strain - STEEL PLATE
usp_strain = 0.1  # Ultimate strain - STEEL PLATE

ys_strain = 0.02 # Yield strain - STEEL REBAR
us_strain = 0.1  # Ultimate strain - STEEL REBAR

yc_strain = 0.0002 # Yield strain - CONFINED CONCRETE
uc_strain = 0.008  # Ultimate strain -  CONFINED CONCRETE

# Number of nodes
num_nodes = 101

NUM_ITERATION = 50
for i in range(NUM_ITERATION):
    period.append(T[i])
    nf.append(1/T[i])
    pgd.append(MAXABS_FUN(DATA_FILE01, 1, i, _, 1))# MAX ABS DISPLACEMENT OF NODE 16
    pgv.append(MAXABS_FUN(DATA_FILE02, 1, i, _, 1))# MAX ABS VELOCITY OF NODE 16
    pga.append(MAXABS_FUN(DATA_FILE03, 1, i, _, 1))# MAX ABS ACCELERATION OF NODE 16
    base01 = OUTPUT_SECOND_COLUMN(FOLDER_NAME,'BTH_DYN_01', 2, i, 2) # Reading base shear from Text file - DYNAMIC - NODE 1
    base02 = OUTPUT_SECOND_COLUMN(FOLDER_NAME,'BTH_DYN_101', 2, i, 2) # Reading base shear from Text file - DYNAMIC - NODE 101
    baseD = max(abs(base01 + base02))
    pgb.append(baseD)
    # STRUCTURE DUCTILITY DAMAGE INDEX
    dispP = OUTPUT_SECOND_COLUMN(FOLDER_NAME,'DTH_PUSH', 2, i, 2) # Reading Disp from Text file - PUSHOVER
    base01 = OUTPUT_SECOND_COLUMN(FOLDER_NAME,'BTH_PUSH_01', 2, i, 2) # Reading base shear from Text file - PUSHOVER - NODE 1
    base02 = OUTPUT_SECOND_COLUMN(FOLDER_NAME,'BTH_PUSH_101', 2, i, 2) # Reading base shear from Text file - PUSHOVER - NODE 101
    dispP = np.abs(dispP); baseP = np.abs(base01 + base02); # ABSOLUTE VALUE
    bDbP.append(pgb[-1] / max(baseP))
    dDdP.append(pgd[-1] / max(dispP))
    xx, yy, Elastic_EI, Plastic_EI, Tangent_EI, Ductility_Rito, Over_Stregth_Factor = BILNEAR_CURVE(dispP, baseP, 30) 
    xx = np.abs(xx); yy = np.abs(yy) # ABSOLUTE VALUE
    osf.append(Over_Stregth_Factor)
    dr.append(Ductility_Rito)
    pei.append(Plastic_EI)
    eei.append(Elastic_EI)
    yd.append(xx[1])
    yb.append(yy[1])
    ud.append(xx[2])
    ub.append(yy[2])
    demand_disp = MAXABS_FUN(DATA_FILE01, 1, i, _, 1)# DISPLACEMENT DYNAMIC ANALYSIS
    DIs = (demand_disp - xx[1]) / (xx[2] - xx[1])
    #DIs = (demand_disp - xx[1]) / (abs(DMAX) - xx[1]) # IF xx[2] MORE THAN DMAX YOU MUST USE THIS 
    diS.append(DIs)
    # SECTION DUCTILITY DAMAGE INDEX
    DEMAND_CURVATURE = MAXABS_FUN(DATA_FILE11, 1, i, _, 1)# CURVATURE DYNAMIC ANALYSIS
    DIc = (DEMAND_CURVATURE - xxc[1]) / (xxc[2] - xxc[1]) # Target Section Ductility Damage Index
    diC.append(DIc)
    # AXIAL DUCTILITY DAMAGE INDEX - CONCRETE
    DEMAND_STRAIN = max(abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,'DYN_fiberCon_StressStrain_01', 1, i, 2)))
    DEMAND_STRESS = max(abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,'DYN_fiberCon_StressStrain_01', 0, i, 2)))
    Dyn_fiber_C_Strain01.append(DEMAND_STRAIN)
    Dyn_fiber_C_Stress01.append(DEMAND_STRESS)
    DI_AXIAL = (DEMAND_STRAIN - ys_strain) / (us_strain - ys_strain)# Axial Ductility Damage Index for Concrete Fiber 01
    diAC01.append(DI_AXIAL)
    DEMAND_STRAIN = max(abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,'DYN_fiberCon_StressStrain_02', 1, i, 2)))
    DEMAND_STRESS = max(abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,'DYN_fiberCon_StressStrain_02', 0, i, 2)))
    Dyn_fiber_C_Strain02.append(DEMAND_STRAIN)
    Dyn_fiber_C_Stress02.append(DEMAND_STRESS)
    DI_AXIAL = (DEMAND_STRAIN - ys_strain) / (us_strain - ys_strain)# Axial Ductility Damage Index for Steel Rebar Fiber 02
    diAC02.append(DI_AXIAL)
    DEMAND_STRAIN = max(abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,'DYN_fiberCon_StressStrain_03', 1, i, 2)))
    DEMAND_STRESS = max(abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,'DYN_fiberCon_StressStrain_03', 0, i, 2)))
    Dyn_fiber_C_Strain03.append(DEMAND_STRAIN)
    Dyn_fiber_C_Stress03.append(DEMAND_STRESS)
    DI_AXIAL = (DEMAND_STRAIN - ys_strain) / (us_strain - ys_strain)# Axial Ductility Damage Index for Steel Rebar Fiber 03
    diAC03.append(DI_AXIAL)
    # AXIAL DUCTILITY DAMAGE INDEX - REBAR
    DEMAND_STRAIN = np.max(np.abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,'DYN_fiberReb_StressStrain_01', 1, i, 2)))
    DEMAND_STRESS = np.max(np.abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,'DYN_fiberReb_StressStrain_01', 0, i, 2)))
    Dyn_fiber_R_Strain01.append(DEMAND_STRAIN)
    Dyn_fiber_R_Stress01.append(DEMAND_STRESS)
    DI_AXIAL = (DEMAND_STRAIN - ys_strain) / (us_strain - ys_strain)# Axial Ductility Damage Index for Steel Rebar Fiber 01
    diAS01.append(DI_AXIAL)
    DEMAND_STRAIN = np.max(np.abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,f'DYN_fiberReb_StressStrain_02', 1, i, 2)))
    DEMAND_STRESS = np.max(np.abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,f'DYN_fiberReb_StressStrain_02', 0, i, 2)))
    Dyn_fiber_R_Strain02.append(DEMAND_STRAIN)
    Dyn_fiber_R_Stress02.append(DEMAND_STRESS)
    DI_AXIAL = (DEMAND_STRAIN - ys_strain) / (us_strain - ys_strain)# Axial Ductility Damage Index for Steel Rebar Fiber 02
    diAS02.append(DI_AXIAL)
    DEMAND_STRAIN = np.max(np.abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,f'DYN_fiberReb_StressStrain_03', 1, i, 2)))
    DEMAND_STRESS = np.max(np.abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,f'DYN_fiberReb_StressStrain_03', 0, i, 2)))
    Dyn_fiber_R_Strain03.append(DEMAND_STRAIN)
    Dyn_fiber_R_Stress03.append(DEMAND_STRESS)
    DI_AXIAL = (DEMAND_STRAIN - ys_strain) / (us_strain - ys_strain)# Axial Ductility Damage Index for Steel Rebar Fiber 03
    diAS03.append(DI_AXIAL)
    DEMAND_STRAIN = np.max(np.abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,f'DYN_fiberReb_StressStrain_04', 1, i, 2)))
    DEMAND_STRESS = np.max(np.abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,f'DYN_fiberReb_StressStrain_04', 0, i, 2)))
    Dyn_fiber_R_Strain04.append(DEMAND_STRAIN)
    Dyn_fiber_R_Stress04.append(DEMAND_STRESS)
    DI_AXIAL = (DEMAND_STRAIN - ys_strain) / (us_strain - ys_strain)# Axial Ductility Damage Index for Steel Rebar Fiber 04
    diAS04.append(DI_AXIAL)
    DEMAND_STRAIN = np.max(np.abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,f'DYN_fiberReb_StressStrain_05', 1, i, 2)))
    DEMAND_STRESS = np.max(np.abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,f'DYN_fiberReb_StressStrain_05', 0, i, 2)))
    Dyn_fiber_R_Strain05.append(DEMAND_STRAIN)
    Dyn_fiber_R_Stress05.append(DEMAND_STRESS)
    DI_AXIAL = (DEMAND_STRAIN - ys_strain) / (us_strain - ys_strain)# Axial Ductility Damage Index for Steel Rebar Fiber 05
    diAS05.append(DI_AXIAL)
    # AXIAL DUCTILITY DAMAGE INDEX - PLATE
    DEMAND_STRAIN = np.max(np.abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,'DYN_fiberPlate_StressStrain_01', 1, i, 2)))
    DEMAND_STRESS = np.max(np.abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,'DYN_fiberPlate_StressStrain_01', 0, i, 2)))
    Dyn_fiber_P_Strain01.append(DEMAND_STRAIN)
    Dyn_fiber_P_Stress01.append(DEMAND_STRESS)
    DI_AXIAL = (DEMAND_STRAIN - ysp_strain) / (usp_strain - ysp_strain)# Axial Ductility Damage Index for Steel Plate Fiber
    diASP01.append(DI_AXIAL)
    DEMAND_STRAIN = np.max(np.abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,'DYN_fiberPlate_StressStrain_02', 1, i, 2)))
    DEMAND_STRESS = np.max(np.abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,'DYN_fiberPlate_StressStrain_02', 0, i, 2)))
    Dyn_fiber_P_Strain02.append(DEMAND_STRAIN)
    Dyn_fiber_P_Stress02.append(DEMAND_STRESS)
    DI_AXIAL = (DEMAND_STRAIN - ysp_strain) / (usp_strain - ysp_strain)# Axial Ductility Damage Index for Steel Plate Fiber
    diASP02.append(DI_AXIAL)  
    print(f'{i+1} T: {period[-1]:.5e} pgd: {pgd[-1]:.5e} pgv: {pgv[-1]:.5e} pga: {pga[-1]:.5e} pgb: {pgb[-1]:.5e}')

1 T: 2.53200e-01 pgd: 2.02100e+01 pgv: 5.41841e-04 pga: 1.35887e-02 pgb: 6.72706e+06
2 T: 2.53200e-01 pgd: 2.02100e+01 pgv: 1.08368e-03 pga: 2.71775e-02 pgb: 6.72706e+06
3 T: 2.53200e-01 pgd: 2.02100e+01 pgv: 1.62552e-03 pga: 4.07662e-02 pgb: 6.72708e+06
4 T: 2.53200e-01 pgd: 2.02100e+01 pgv: 2.16736e-03 pga: 5.43549e-02 pgb: 6.72708e+06
5 T: 2.53200e-01 pgd: 2.02100e+01 pgv: 2.70920e-03 pga: 6.79437e-02 pgb: 6.72708e+06
6 T: 2.53200e-01 pgd: 2.02101e+01 pgv: 3.25104e-03 pga: 8.15324e-02 pgb: 6.72708e+06
7 T: 2.53200e-01 pgd: 2.02101e+01 pgv: 3.79289e-03 pga: 9.51212e-02 pgb: 6.72710e+06
8 T: 2.53200e-01 pgd: 2.02101e+01 pgv: 4.33473e-03 pga: 1.08710e-01 pgb: 6.72710e+06
9 T: 2.53200e-01 pgd: 2.02101e+01 pgv: 4.87657e-03 pga: 1.22299e-01 pgb: 6.72710e+06
10 T: 2.53200e-01 pgd: 2.02102e+01 pgv: 5.41841e-03 pga: 1.35887e-01 pgb: 6.72712e+06
11 T: 2.53200e-01 pgd: 2.02102e+01 pgv: 5.96025e-03 pga: 1.49476e-01 pgb: 6.72712e+06
12 T: 2.53200e-01 pgd: 2.02102e+01 pgv: 6.50209e-03 pga: 1.63065e-01 pgb: 6.72712e+06
13 T: 2.53200e-01 pgd: 2.02102e+01 pgv: 7.04393e-03 pga: 1.76654e-01 pgb: 6.72712e+06
14 T: 2.53200e-01 pgd: 2.02102e+01 pgv: 7.58577e-03 pga: 1.90242e-01 pgb: 6.72714e+06
15 T: 2.53200e-01 pgd: 2.02103e+01 pgv: 8.12761e-03 pga: 2.03831e-01 pgb: 6.72714e+06
16 T: 2.53200e-01 pgd: 2.02103e+01 pgv: 8.66945e-03 pga: 2.17420e-01 pgb: 6.72714e+06
17 T: 2.53200e-01 pgd: 2.02103e+01 pgv: 9.21129e-03 pga: 2.31009e-01 pgb: 6.72716e+06
18 T: 2.53200e-01 pgd: 2.02103e+01 pgv: 9.75313e-03 pga: 2.44597e-01 pgb: 6.72716e+06
19 T: 2.53200e-01 pgd: 2.02103e+01 pgv: 1.02950e-02 pga: 2.58186e-01 pgb: 6.72716e+06
20 T: 2.53200e-01 pgd: 2.02104e+01 pgv: 1.08368e-02 pga: 2.71775e-01 pgb: 6.72716e+06
21 T: 2.53200e-01 pgd: 2.02104e+01 pgv: 1.13787e-02 pga: 2.85364e-01 pgb: 6.72718e+06
22 T: 2.53200e-01 pgd: 2.02104e+01 pgv: 1.19205e-02 pga: 2.98952e-01 pgb: 6.72718e+06
23 T: 2.53200e-01 pgd: 2.02104e+01 pgv: 1.24623e-02 pga: 3.12541e-01 pgb: 6.72718e+06
24 T: 2.53200e-01 pgd: 2.02105e+01 pgv: 1.30042e-02 pga: 3.26130e-01 pgb: 6.72720e+06
25 T: 2.53200e-01 pgd: 2.02105e+01 pgv: 1.35460e-02 pga: 3.39718e-01 pgb: 6.72720e+06
26 T: 2.53200e-01 pgd: 2.02105e+01 pgv: 1.40879e-02 pga: 3.53307e-01 pgb: 6.72720e+06
27 T: 2.53200e-01 pgd: 2.02105e+01 pgv: 1.46297e-02 pga: 3.66896e-01 pgb: 6.72720e+06
28 T: 2.53200e-01 pgd: 2.02105e+01 pgv: 1.51715e-02 pga: 3.80485e-01 pgb: 6.72722e+06
29 T: 2.53200e-01 pgd: 2.02106e+01 pgv: 1.57134e-02 pga: 3.94073e-01 pgb: 6.72722e+06
30 T: 2.53200e-01 pgd: 2.02106e+01 pgv: 1.62552e-02 pga: 4.07662e-01 pgb: 6.72722e+06
31 T: 2.53200e-01 pgd: 2.02106e+01 pgv: 1.67971e-02 pga: 4.21251e-01 pgb: 6.72724e+06
32 T: 2.53200e-01 pgd: 2.02106e+01 pgv: 1.73389e-02 pga: 4.34840e-01 pgb: 6.72724e+06
33 T: 2.53200e-01 pgd: 2.02107e+01 pgv: 1.78807e-02 pga: 4.48428e-01 pgb: 6.72724e+06
34 T: 2.53200e-01 pgd: 2.02107e+01 pgv: 1.84226e-02 pga: 4.62017e-01 pgb: 6.72724e+06
35 T: 2.53200e-01 pgd: 2.02107e+01 pgv: 1.89644e-02 pga: 4.75606e-01 pgb: 6.72726e+06
36 T: 2.53200e-01 pgd: 2.02107e+01 pgv: 1.95063e-02 pga: 4.89195e-01 pgb: 6.72726e+06
37 T: 2.53200e-01 pgd: 2.02107e+01 pgv: 2.00481e-02 pga: 5.02783e-01 pgb: 6.72726e+06
38 T: 2.53200e-01 pgd: 2.02108e+01 pgv: 2.05899e-02 pga: 5.16372e-01 pgb: 6.72728e+06
39 T: 2.53200e-01 pgd: 2.02108e+01 pgv: 2.11318e-02 pga: 5.29961e-01 pgb: 6.72728e+06
40 T: 2.53200e-01 pgd: 2.02108e+01 pgv: 2.16736e-02 pga: 5.43549e-01 pgb: 6.72728e+06
41 T: 2.53200e-01 pgd: 2.02108e+01 pgv: 2.22155e-02 pga: 5.57138e-01 pgb: 6.72730e+06
42 T: 2.53200e-01 pgd: 2.02109e+01 pgv: 2.27573e-02 pga: 5.70727e-01 pgb: 6.72730e+06
43 T: 2.53200e-01 pgd: 2.02109e+01 pgv: 2.32992e-02 pga: 5.84316e-01 pgb: 6.72730e+06
44 T: 2.53200e-01 pgd: 2.02109e+01 pgv: 2.38410e-02 pga: 5.97904e-01 pgb: 6.72730e+06
45 T: 2.53200e-01 pgd: 2.02109e+01 pgv: 2.43828e-02 pga: 6.11493e-01 pgb: 6.72732e+06
46 T: 2.53200e-01 pgd: 2.02109e+01 pgv: 2.49247e-02 pga: 6.25082e-01 pgb: 6.72732e+06
47 T: 2.53200e-01 pgd: 2.02110e+01 pgv: 2.54665e-02 pga: 6.38671e-01 pgb: 6.72732e+06
48 T: 2.53200e-01 pgd: 2.02110e+01 pgv: 2.60084e-02 pga: 6.52259e-01 pgb: 6.72734e+06
49 T: 2.53200e-01 pgd: 2.02110e+01 pgv: 2.65502e-02 pga: 6.65848e-01 pgb: 6.72734e+06
50 T: 2.53200e-01 pgd: 2.02110e+01 pgv: 2.70920e-02 pga: 6.79437e-01 pgb: 6.72734e+06

xlabel = 'Amplified Factor due to Acceleration Gravity'
y1label = 'Displacement'
y2label = 'Velocity'
y3label = 'Acceleration'
y4label = 'Base-shear'
PLOT_TIME_HIS(AF, xlabel, pgd, y1label, pgv, y2label, pga, y3label, pgb, y4label, Z=4, LOGX=0, LOGY=0)

# Data usage
X = AF
Y = diS
XLABEL = 'ACCELERATION GRAVITY AMPLIFIED FACTOR'
YLABEL = 'STRUCTURAL DUCTILITY DAMAGE INDEX'
TITLE = 'Structural Ductility Damage Index on Composite Bridge Response Spectrum'
LABELS = 'DI'
COLOR='purple'

PLOT_SCATTER(AF, diS, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 7) 
#PLOT_SCATTER_PLOTLY(AF, diS, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 7)

# Data usage
XLABEL = 'ACCELERATION GRAVITY AMPLIFIED FACTOR'
YLABEL = 'SECTION DUCTILITY DAMAGE INDEX'
TITLE = 'Section Ductility Damage Index on Composite Bridge Response Spectrum'
LABELS = 'DI'
COLOR='gold'

PLOT_SCATTER(AF, diC, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 7) 
#PLOT_SCATTER_PLOTLY(AF, diC, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 7)

XLABEL = 'ACCELERATION GRAVITY AMPLIFIED FACTOR'
YLABEL = 'STRUCTURE OVERSTRENGTH FACTOR'
TITLE = 'Composite Bridge Response Spectrum'
COLOR = 'lime'

PLOT_SCATTER(AF, osf, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1) 
#PLOT_SCATTER_PLOTLY(AF, osf, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1)

XLABEL = 'ACCELERATION GRAVITY AMPLIFIED FACTOR'
YLABEL = 'STRUCTURE DUCTILITY RATIO'
TITLE = 'Composite Bridge Response Spectrum'
COLOR = 'pink'

PLOT_SCATTER(AF, dr, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1) 
#PLOT_SCATTER_PLOTLY(AF, dr, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1)

XLABEL = 'ACCELERATION GRAVITY AMPLIFIED FACTOR'
YLABEL = 'Elastic Flexural Rigidity of Structure'
TITLE = 'Composite Bridge Response Spectrum'
COLOR = 'red'

PLOT_SCATTER(AF, eei, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1) 
#PLOT_SCATTER_PLOTLY(AF, eei, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1)

C:\Users\Dell\AppData\Local\Temp\ipykernel_8624\4171905578.py:315: RuntimeWarning:

divide by zero encountered in scalar divide

XLABEL = 'ACCELERATION GRAVITY AMPLIFIED FACTOR'
YLABEL = 'Plastic Flexural Rigidity of Structure'
TITLE = 'Composite Bridge Response Spectrum'
COLOR = 'green'

PLOT_SCATTER(AF, pei, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1) 
#PLOT_SCATTER_PLOTLY(AF, pei, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1)

XLABEL = 'ACCELERATION GRAVITY AMPLIFIED FACTOR'
YLABEL = 'Yield Displacement of Structure'
TITLE = 'Composite Bridge Response Spectrum'
COLOR = 'brown'

PLOT_SCATTER(AF, yd, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1) 
#PLOT_SCATTER_PLOTLY(AF, yd, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1)

XLABEL = 'ACCELERATION GRAVITY AMPLIFIED FACTOR'
YLABEL = 'Yield Base-Shear of Structure'
TITLE = 'Composite Bridge Response Spectrum'
COLOR = 'blue'

PLOT_SCATTER(AF, yb, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1) 
#PLOT_SCATTER_PLOTLY(AF, yb, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1)

XLABEL = 'ACCELERATION GRAVITY AMPLIFIED FACTOR'
YLABEL = 'Utilamte Displacement of Structure'
TITLE = 'Composite Bridge Response Spectrum'
COLOR = 'orange'

PLOT_SCATTER(AF, ud, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1) 
#PLOT_SCATTER_PLOTLY(AF, ud, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1)

C:\Users\Dell\AppData\Local\Temp\ipykernel_8624\4171905578.py:315: RuntimeWarning:

invalid value encountered in scalar divide

XLABEL = 'ACCELERATION GRAVITY AMPLIFIED FACTOR'
YLABEL = 'Utilamte Base-Shear of Structure'
TITLE = 'Composite Bridge Response Spectrum'
COLOR = 'green'

PLOT_SCATTER(AF, ub, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1) 
#PLOT_SCATTER_PLOTLY(AF, ub, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1)

C:\Users\Dell\AppData\Local\Temp\ipykernel_8624\4171905578.py:315: RuntimeWarning:

divide by zero encountered in scalar divide

# Data usage
x = AF
y_list = [
    Dyn_fiber_C_Strain01,
    Dyn_fiber_C_Strain02,
    Dyn_fiber_C_Strain03,

]

XLABEL = 'ACCELERATION GRAVITY AMPLIFIED FACTOR'
YLABEL = 'CONCRETE STRIAN'
TITLE = 'Concrete Strain on Composite Bridge'
LABELS = ['LAYER 01', 'LAYER 02','LAYER 03']
plot_multiple_lines(x, y_list, LABELS, XLABEL, YLABEL, TITLE)

# Data usage
x = AF
y_list = [
    diAC01,
    diAC02,
    diAC03,

]

XLABEL = 'ACCELERATION GRAVITY AMPLIFIED FACTOR'
YLABEL = 'CONCRETE AXIAL DUCTILITY DAMAGE INDEX'
TITLE = 'Concrete Axial Ductility Damage Index on Composite Bridge'
LABELS = ['LAYER 01', 'LAYER 02','LAYER 03']
plot_multiple_lines(x, y_list, LABELS, XLABEL, YLABEL, TITLE)

# Data usage
x = AF
y_list = [
    Dyn_fiber_R_Strain01,
    Dyn_fiber_R_Strain02,
    Dyn_fiber_R_Strain03,
    Dyn_fiber_R_Strain04,
    Dyn_fiber_R_Strain05,

]

XLABEL = 'ACCELERATION GRAVITY AMPLIFIED FACTOR'
YLABEL = 'STEEL REBAR STRIAN'
TITLE = 'Steel Rebar Strain on Composite Bridge'
LABELS = ['LAYER 01', 'LAYER 02','LAYER 03', 'LAYER 04', 'LAYER 05']
plot_multiple_lines(x, y_list, LABELS, XLABEL, YLABEL, TITLE)

# Data usage
x = AF
y_list = [
    diAS01,
    diAS02,
    diAS03,
    diAS04, 
    diAS05
]

XLABEL = 'ACCELERATION GRAVITY AMPLIFIED FACTOR'
YLABEL = 'REBAR AXIAL DUCTILITY DAMAGE INDEX'
TITLE = 'Steel Rebar Axial Ductility Damage Index on Composite Bridge'
LABELS = ['LAYER 01', 'LAYER 02','LAYER 03', 'LAYER 04', 'LAYER 05']
plot_multiple_lines(x, y_list, LABELS, XLABEL, YLABEL, TITLE)

# Data usage
x = AF
y_list = [
    Dyn_fiber_P_Strain01,
    Dyn_fiber_P_Strain02,
]

XLABEL = 'ACCELERATION GRAVITY AMPLIFIED FACTOR'
YLABEL = 'STEEL PLATE STRIAN'
TITLE = 'Steel Plate Strain on Composite Bridge'
LABELS = ['LAYER 01', 'LAYER 02']
plot_multiple_lines(x, y_list, LABELS, XLABEL, YLABEL, TITLE)

# Data usage
x = AF
y_list = [
    diASP01,
    diASP02,

]

XLABEL = 'ACCELERATION GRAVITY AMPLIFIED FACTOR'
YLABEL = 'PLATE AXIAL DUCTILITY DAMAGE INDEX'
TITLE = 'Plate Axial Ductility Damage Index on Composite Bridge'
LABELS = ['LAYER 01', 'LAYER 02']
plot_multiple_lines(x, y_list, LABELS, XLABEL, YLABEL, TITLE)

XLABEL = 'ACCELERATION GRAVITY AMPLIFIED FACTOR'
y1label = 'Ratio Base-shear Dynamic to Base-shear Pushover'
y2label = 'Ratio Displacement Dynamic to Displacement Pushover'
PLOT_TIME_HIS(AF, xlabel, bDbP, y1label, dDdP, y2label, _, _, _, _, Z = 2, LOGX = 0, LOGY = 0)

# Data usage
X = dDdP
Y = bDbP
XLABEL = 'DISP DYN/PUSH'
YLABEL = 'BASE-SHEAR DYN/PUSH'
TITLE = 'Displacement and Base-Shear Dynamic to Pushover Ratio on Composite Bridge'
COLOR = 'YELLOW'
PLOT_SCATTER(X, Y, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 3)

C:\Users\Dell\AppData\Local\Temp\ipykernel_8624\4171905578.py:275: RankWarning:

Polyfit may be poorly conditioned

HISROGRAM_BOXPLOT(pgd, HISTO_COLOR='blue', LABEL='Displacement')

-------------------------
Box-Chart Datas: 
Minimum: 20.2100
First quartile: 20.2102
Median: 20.2105
Mean: 20.2105
Std: 0.0003
Third quartile: 20.2108
Maximum: 20.2110
Skewness: 0.0200
kurtosis: -1.2201
90% Confidence Interval: (20.2100, 20.2110)
-------------------------

HISROGRAM_BOXPLOT(pgv, HISTO_COLOR='purple', LABEL='Velocity')

-------------------------
Box-Chart Datas: 
Minimum: 0.0005
First quartile: 0.0072
Median: 0.0138
Mean: 0.0138
Std: 0.0078
Third quartile: 0.0205
Maximum: 0.0271
Skewness: -0.0000
kurtosis: -1.2010
90% Confidence Interval: (0.0019, 0.0258)
-------------------------

HISROGRAM_BOXPLOT(pgd, HISTO_COLOR='blue', LABEL='Displacement')

HISROGRAM_BOXPLOT(pgb, HISTO_COLOR='orange', LABEL='Base-shear')

XLABEL = 'Displacement'
YLABEL = 'Acceleration'
TITLE = '2D CHART'
COLOR = 'purple'
PLOT_SCATTER(pgd, pga, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 7) 
#PLOT_SCATTER_PLOTLY(pgd, pga, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 7)

C:\Users\Dell\AppData\Local\Temp\ipykernel_10664\4171905578.py:275: RankWarning:

Polyfit may be poorly conditioned

XLABEL = 'Displacement'
YLABEL = 'Velocity'
TITLE = '2D CHART'
COLOR = 'orange'
PLOT_SCATTER(pgd, pgv, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 7) 
#PLOT_SCATTER_PLOTLY(pgd, pgv, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 7)

C:\Users\Dell\AppData\Local\Temp\ipykernel_8624\4171905578.py:275: RankWarning:

Polyfit may be poorly conditioned

XLABEL = 'Displacement'
YLABEL = 'Velocity'
ZLABEL = 'Acceleration'
TITLE = '3D CHART'
PLOT3D(pgd, pgv, pga, XLABEL, YLABEL, ZLABEL, TITLE)

XLABEL = 'Axial Ductility Damage Index for Concrete Fiber 01'
YLABEL ='Structure Ductility Damage Index'
TITLE = '2D CHART'
COLOR = 'lightblue'
PLOT_SCATTER(diAC01, diS, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1) 
#PLOT_SCATTER_PLOTLY(diAC01, diS, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1)

XLABEL = 'Axial Ductility Damage Index for Steel Rebar Fiber 01'
YLABEL ='Structure Ductility Damage Index'
TITLE = '2D CHART'
COLOR = 'red'
PLOT_SCATTER(diAS01, diS, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1) 
#PLOT_SCATTER_PLOTLY(diAS01, diS, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1)

XLABEL = 'Axial Ductility Damage Index for Steel Plate Fiber 01'
YLABEL ='Structure Ductility Damage Index'
TITLE = '2D CHART'
COLOR = 'purple'
PLOT_SCATTER(diASP01, diS, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1) 
#PLOT_SCATTER_PLOTLY(diASP01, diS, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1)

XLABEL = 'Structure Ductility Damage Index'
YLABEL = 'Displacement'
TITLE = '2D CHART'
COLOR = 'gray'
PLOT_SCATTER(diS, pgd, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1) 
#PLOT_SCATTER_PLOTLY(diS, pgd, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1)

XLABEL = 'Structure Ductility Damage Index'
YLABEL = 'Velocity'
TITLE = '2D CHART'
COLOR = 'blue'
PLOT_SCATTER(diS, pgv, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1) 
#PLOT_SCATTER_PLOTLY(diS, pgv, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1)

XLABEL = 'Structure Ductility Damage Index'
YLABEL = 'Acceleration'
TITLE = '2D CHART'
COLOR = 'purple'
PLOT_SCATTER(diS, pga, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1) 
#PLOT_SCATTER_PLOTLY(diS, pga, XLABEL, YLABEL, TITLE, COLOR, LOG = 0, ORDER = 1)

### LAST LOAD DATA
import numpy as np
## PYSHOVER ANALYSIS DATA
# Displacement Time History
DTHP = OUTPUT_SECOND_COLUMN(FOLDER_NAME,'DTH_PUSH', 2, i, 2)
# Base Shear Time History 01
BTH01 = OUTPUT_SECOND_COLUMN(FOLDER_NAME,'BTH_PUSH_01', 2, i, 2)
# Base Shear Time History 101
BTH0101 = OUTPUT_SECOND_COLUMN(FOLDER_NAME,'BTH_PUSH_101', 2, i, 2)

BTHP = abs(BTH01 + BTH0101)

print(len(DTHP), len(BTHP))

## DYNAMAIC ANALYSIS DATA
# Displacement Time History
DTHD = OUTPUT_SECOND_COLUMN(FOLDER_NAME,'DTH_DYN', 2, i, 2)
# Velocity Time History
VTH = OUTPUT_SECOND_COLUMN(FOLDER_NAME,'VTH_DYN', 2, i, 2)
# Acceleration Time History
ATH = OUTPUT_SECOND_COLUMN(FOLDER_NAME,'ATH_DYN', 2, i, 2)
# Base Shear Time History 01
BTH01 = OUTPUT_SECOND_COLUMN(FOLDER_NAME,'BTH_DYN_01', 2, i, 2)
# Base Shear Time History 101
BTH0101 = OUTPUT_SECOND_COLUMN(FOLDER_NAME,'BTH_DYN_101', 2, i, 2)
# Total Base Shear
BTHD = BTH01 + BTH0101

print(len(DTHD), len(VTH),len(ATH),len(BTHD))

1010 1010
1010 1010 1010 1010

print(len(BTHP))
print(len(BTHD), len(DTHD))
xx, yy, _, _, _, _, _ = BILNEAR_CURVE(abs(DTHP), abs(BTHP), 30)
print(yy[1]/ xx[1])
#demand_disp = MAXABS_FUN(DATA_FILE01, 1, i)# DEMAND DYNAMIC DISPLACEMENT
XLABEL = 'Displacement'
YLABEL = 'Base Shear'
TITLE = 'Last Data Base-Shear and Displacement Pushover Analysis'
LEGEND01 = 'Pushover'
LEGEND02 = 'Bilinear Fitted'
LEGEND03 = 'Dynamic'
COLOR = 'black'
PLOT_2D(abs(DTHP), abs(BTHP), xx, yy, abs(DTHD), abs(BTHD), XLABEL, YLABEL, TITLE, LEGEND01, LEGEND02, LEGEND03, COLOR='black', Z=3) 
DIs = (demand_disp - xx[1]) / (xx[2] - xx[1])
print(f'\t\t\t Structure Ductility Damage Index: {DIs:.3f}')
print(f'\t\t\t Structure Ductility ratio: {xx[2] / xx[1]:.3f}')

1010
1010 1010
315607.9435271555

			 Structure Ductility Damage Index: -0.268
			 Structure Ductility ratio: 3.280

xlabel = 'Time'
y1label = 'Displacement Time History'
y2label = 'Velocity Time History'
y3label = 'Acceleration Time History'
y4label = 'Base-shear  Time History'
MAX_TIME = 10 # DATA MUST BE GOTTEN FROM GROUND MOTION TIME HISTORY
DT  = MAX_TIME / len(DTHD)
TIME = np.arange(0, MAX_TIME , DT)
print(len(TIME))
PLOT_TIME_HIS(TIME, xlabel, DTHD, y1label, VTH, y2label, ATH, y3label, BTHD, y4label, Z = 4, LOGX = 0, LOGY = 0)

1010

# OUTPUT SHEAR AND MOMENT FOR LAST ANALYSIS DATA ELEMENT
# 49 IS THE LAST OUTPUT DATA
NodeJOINT = [] # Joint Counts
AXIAL_P = [] # Internal Shear Force - PUSHOVER
SHEAR_P = [] # Internal Shear Force - PUSHOVER
MOMENT_P = [] # Internal Moment Force - PUSHOVER
AXIAL_D = [] # Internal Shear Force - DYNAMIC
SHEAR_D = [] # Internal Shear Force - DYNAMIC
MOMENT_D = [] # Internal Moment Force - DYNAMIC
II = NUM_ITERATION-1 # LAST COUNT ANALYSIS
for i in range(0, num_nodes-1):
    NodeJOINT.append(i+1)
    # PUSHOVER
    axial_P = np.max(np.abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,f'LOCALFORCE_PUSH_{i}', 4, II, 2))) # Element Internal Force - Axial
    shear_P = np.max(np.abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,f'LOCALFORCE_PUSH_{i}', 5, II, 2))) # Element Internal Force - Shear
    moment_P = np.max(np.abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,f'LOCALFORCE_PUSH_{i}', 6, II, 2))) # Element Internal Force - Moment
    AXIAL_P.append(axial_P);SHEAR_P.append(shear_P);MOMENT_P.append(moment_P);
    # DYNAMIC
    axial_D = np.max(np.abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,f'LOCALFORCE_DYN_{i}', 4, II, 2))) # Element Internal Force - Axial
    shear_D = np.max(np.abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,f'LOCALFORCE_DYN_{i}', 5, II, 2))) # Element Internal Force - Shear
    moment_D = np.max(np.abs(OUTPUT_SECOND_COLUMN(FOLDER_NAME,f'LOCALFORCE_DYN_{i}', 6, II, 2))) # Element Internal Force - Moment
    AXIAL_D.append(axial_D);SHEAR_D.append(shear_D);MOMENT_D.append(moment_D);
    print(i+1)

# Data usage
x = NodeJOINT

XLABEL = 'BRIDGE NODE'
YLABEL = 'AXIAL'
TITLE = 'Pushover Analysis Axial Diagram on Composite Bridge Deck'
LABELS = ''
PLOT_2D(NodeJOINT, AXIAL_P, _, _, _, _, XLABEL, YLABEL, TITLE, _, _, _, COLOR='red', Z=1)

# Data usage
x = NodeJOINT

XLABEL = 'BRIDGE NODE'
YLABEL = 'AXIAL'
TITLE = 'Dynamic Analysis Axial Diagram on Composite Bridge Deck'
LABELS = ''
PLOT_2D(NodeJOINT, AXIAL_D, _, _, _, _, XLABEL, YLABEL, TITLE, _, _, _, COLOR='blue', Z=1)

# Data usage
x = NodeJOINT

XLABEL = 'BRIDGE NODE'
YLABEL = 'SHEAR'
TITLE = 'Pushover Analysis Shear Diagram on Composite Bridge Deck'
LABELS = ''
PLOT_2D(NodeJOINT, SHEAR_P, _, _, _, _, XLABEL, YLABEL, TITLE, _, _, _, COLOR='purple', Z=1)

# Data usage
x = NodeJOINT

XLABEL = 'BRIDGE NODE'
YLABEL = 'SHEAR'
TITLE = 'Dynamic Analysis Shear Diagram on Composite Bridge Deck'
LABELS = ''
PLOT_2D(NodeJOINT, SHEAR_D, _, _, _, _, XLABEL, YLABEL, TITLE, _, _, _, COLOR='green', Z=1)

# Data usage
x = NodeJOINT

XLABEL = 'BRIDGE NODE'
YLABEL = 'MOMENT'
TITLE = 'Pushover Analysis Moment Diagram on Composite Bridge Deck'
LABELS = ''
PLOT_2D(NodeJOINT, MOMENT_P, _, _, _, _, XLABEL, YLABEL, TITLE, _, _, _, COLOR='purple', Z=1)

# Data usage
x = NodeJOINT

XLABEL = 'BRIDGE NODE'
YLABEL = 'MOMENT'
TITLE = 'Dynamic Analysis Moment Diagram on Composite Bridge Deck'
LABELS = ''
PLOT_2D(NodeJOINT, MOMENT_D, _, _, _, _, XLABEL, YLABEL, TITLE, _, _, _, COLOR='green', Z=1)

import pandas as pd
# Create a DataFrame
df = pd.DataFrame({'Displacement Response Spectrum': pgd,
                   'Velocity Response Spectrum': pgv,
                   'Acceleration Response Spectrum': pga,
                   'Base-shear Response Spectrum': pgb,
                   'Structure Ductility Damage Index Response Spectrum': diS,
                   'Section Ductility Damage Index Response Spectrum': diC,
                   'Concrete Axial Ductility Damage Index Response Spectrum Fiber 01':diAC01,
                   'Steel Rebar Axial Ductility Damage Index Response Spectrum Fiber 01':diAS01,
                   'Steel Plate Axial Ductility Damage Index Response Spectrum Fiber 01':diASP01})
print(df)
# PLOT HEATMAP FOR CORRELATION 
PLOT_HEATMAP(df)

    Displacement Response Spectrum  Velocity Response Spectrum  \
0                          20.2100                    0.000542   
1                          20.2100                    0.001084   
2                          20.2100                    0.001626   
3                          20.2100                    0.002167   
4                          20.2100                    0.002709   
5                          20.2101                    0.003251   
6                          20.2101                    0.003793   
7                          20.2101                    0.004335   
8                          20.2101                    0.004877   
9                          20.2102                    0.005418   
10                         20.2102                    0.005960   
11                         20.2102                    0.006502   
12                         20.2102                    0.007044   
13                         20.2102                    0.007586   
14                         20.2103                    0.008128   
15                         20.2103                    0.008669   
16                         20.2103                    0.009211   
17                         20.2103                    0.009753   
18                         20.2103                    0.010295   
19                         20.2104                    0.010837   
20                         20.2104                    0.011379   
21                         20.2104                    0.011921   
22                         20.2104                    0.012462   
23                         20.2105                    0.013004   
24                         20.2105                    0.013546   
25                         20.2105                    0.014088   
26                         20.2105                    0.014630   
27                         20.2105                    0.015171   
28                         20.2106                    0.015713   
29                         20.2106                    0.016255   
30                         20.2106                    0.016797   
31                         20.2106                    0.017339   
32                         20.2107                    0.017881   
33                         20.2107                    0.018423   
34                         20.2107                    0.018964   
35                         20.2107                    0.019506   
36                         20.2107                    0.020048   
37                         20.2108                    0.020590   
38                         20.2108                    0.021132   
39                         20.2108                    0.021674   
40                         20.2108                    0.022215   
41                         20.2109                    0.022757   
42                         20.2109                    0.023299   
43                         20.2109                    0.023841   
44                         20.2109                    0.024383   
45                         20.2109                    0.024925   
46                         20.2110                    0.025466   
47                         20.2110                    0.026008   
48                         20.2110                    0.026550   
49                         20.2110                    0.027092   

    Acceleration Response Spectrum  Base-shear Response Spectrum  \
0                         0.013589                     6727060.0   
1                         0.027178                     6727060.0   
2                         0.040766                     6727080.0   
3                         0.054355                     6727080.0   
4                         0.067944                     6727080.0   
5                         0.081532                     6727080.0   
6                         0.095121                     6727100.0   
7                         0.108710                     6727100.0   
8                         0.122299                     6727100.0   
9                         0.135887                     6727120.0   
10                        0.149476                     6727120.0   
11                        0.163065                     6727120.0   
12                        0.176654                     6727120.0   
13                        0.190242                     6727140.0   
14                        0.203831                     6727140.0   
15                        0.217420                     6727140.0   
16                        0.231009                     6727160.0   
17                        0.244597                     6727160.0   
18                        0.258186                     6727160.0   
19                        0.271775                     6727160.0   
20                        0.285364                     6727180.0   
21                        0.298952                     6727180.0   
22                        0.312541                     6727180.0   
23                        0.326130                     6727200.0   
24                        0.339718                     6727200.0   
25                        0.353307                     6727200.0   
26                        0.366896                     6727200.0   
27                        0.380485                     6727220.0   
28                        0.394073                     6727220.0   
29                        0.407662                     6727220.0   
30                        0.421251                     6727240.0   
31                        0.434840                     6727240.0   
32                        0.448428                     6727240.0   
33                        0.462017                     6727240.0   
34                        0.475606                     6727260.0   
35                        0.489195                     6727260.0   
36                        0.502783                     6727260.0   
37                        0.516372                     6727280.0   
38                        0.529961                     6727280.0   
39                        0.543549                     6727280.0   
40                        0.557138                     6727300.0   
41                        0.570727                     6727300.0   
42                        0.584316                     6727300.0   
43                        0.597904                     6727300.0   
44                        0.611493                     6727320.0   
45                        0.625082                     6727320.0   
46                        0.638671                     6727320.0   
47                        0.652259                     6727340.0   
48                        0.665848                     6727340.0   
49                        0.679437                     6727340.0   

    Structure Ductility Damage Index Response Spectrum  \
0                                           -0.267754    
1                                           -0.267754    
2                                           -0.267754    
3                                           -0.267754    
4                                           -0.267754    
5                                           -0.267753    
6                                           -0.267753    
7                                           -0.267753    
8                                           -0.267753    
9                                           -0.267753    
10                                          -0.267753    
11                                          -0.267753    
12                                          -0.267753    
13                                          -0.267753    
14                                          -0.267752    
15                                          -0.267752    
16                                          -0.267752    
17                                          -0.267752    
18                                          -0.267752    
19                                          -0.267751    
20                                          -0.267751    
21                                          -0.267751    
22                                          -0.267751    
23                                          -0.267750    
24                                          -0.267750    
25                                          -0.267750    
26                                          -0.267750    
27                                          -0.267750    
28                                          -0.267749    
29                                          -0.267749    
30                                          -0.267749    
31                                          -0.267749    
32                                          -0.267748    
33                                          -0.267748    
34                                          -0.267748    
35                                          -0.267748    
36                                          -0.267748    
37                                          -0.267748    
38                                          -0.267748    
39                                          -0.267748    
40                                          -0.267748    
41                                          -0.267747    
42                                          -0.267747    
43                                          -0.267747    
44                                          -0.267747    
45                                          -0.267747    
46                                          -0.267746    
47                                          -0.267746    
48                                          -0.267746    
49                                          -0.267746    

    Section Ductility Damage Index Response Spectrum  \
0                                           0.004732   
1                                           0.004732   
2                                           0.004732   
3                                           0.004732   
4                                           0.004732   
5                                           0.004732   
6                                           0.004733   
7                                           0.004733   
8                                           0.004733   
9                                           0.004733   
10                                          0.004733   
11                                          0.004733   
12                                          0.004733   
13                                          0.004733   
14                                          0.004733   
15                                          0.004733   
16                                          0.004733   
17                                          0.004733   
18                                          0.004733   
19                                          0.004733   
20                                          0.004733   
21                                          0.004733   
22                                          0.004733   
23                                          0.004733   
24                                          0.004733   
25                                          0.004733   
26                                          0.004733   
27                                          0.004733   
28                                          0.004733   
29                                          0.004733   
30                                          0.004733   
31                                          0.004733   
32                                          0.004733   
33                                          0.004733   
34                                          0.004733   
35                                          0.004733   
36                                          0.004733   
37                                          0.004733   
38                                          0.004733   
39                                          0.004733   
40                                          0.004733   
41                                          0.004733   
42                                          0.004733   
43                                          0.004733   
44                                          0.004733   
45                                          0.004733   
46                                          0.004734   
47                                          0.004734   
48                                          0.004734   
49                                          0.004734   

    Concrete Axial Ductility Damage Index Response Spectrum Fiber 01  \
0                                           -0.248869                  
1                                           -0.248869                  
2                                           -0.248869                  
3                                           -0.248869                  
4                                           -0.248869                  
5                                           -0.248869                  
6                                           -0.248869                  
7                                           -0.248869                  
8                                           -0.248869                  
9                                           -0.248869                  
10                                          -0.248869                  
11                                          -0.248869                  
12                                          -0.248869                  
13                                          -0.248869                  
14                                          -0.248869                  
15                                          -0.248869                  
16                                          -0.248869                  
17                                          -0.248869                  
18                                          -0.248869                  
19                                          -0.248869                  
20                                          -0.248869                  
21                                          -0.248869                  
22                                          -0.248869                  
23                                          -0.248869                  
24                                          -0.248869                  
25                                          -0.248869                  
26                                          -0.248869                  
27                                          -0.248869                  
28                                          -0.248869                  
29                                          -0.248869                  
30                                          -0.248869                  
31                                          -0.248869                  
32                                          -0.248869                  
33                                          -0.248869                  
34                                          -0.248869                  
35                                          -0.248869                  
36                                          -0.248869                  
37                                          -0.248869                  
38                                          -0.248869                  
39                                          -0.248869                  
40                                          -0.248869                  
41                                          -0.248869                  
42                                          -0.248869                  
43                                          -0.248869                  
44                                          -0.248869                  
45                                          -0.248869                  
46                                          -0.248869                  
47                                          -0.248869                  
48                                          -0.248869                  
49                                          -0.248869                  

    Steel Rebar Axial Ductility Damage Index Response Spectrum Fiber 01  \
0                                           -0.249002                     
1                                           -0.249002                     
2                                           -0.249002                     
3                                           -0.249002                     
4                                           -0.249002                     
5                                           -0.249002                     
6                                           -0.249002                     
7                                           -0.249002                     
8                                           -0.249002                     
9                                           -0.249002                     
10                                          -0.249002                     
11                                          -0.249002                     
12                                          -0.249002                     
13                                          -0.249002                     
14                                          -0.249002                     
15                                          -0.249002                     
16                                          -0.249002                     
17                                          -0.249002                     
18                                          -0.249002                     
19                                          -0.249002                     
20                                          -0.249002                     
21                                          -0.249002                     
22                                          -0.249002                     
23                                          -0.249002                     
24                                          -0.249002                     
25                                          -0.249002                     
26                                          -0.249002                     
27                                          -0.249002                     
28                                          -0.249002                     
29                                          -0.249002                     
30                                          -0.249002                     
31                                          -0.249002                     
32                                          -0.249002                     
33                                          -0.249002                     
34                                          -0.249002                     
35                                          -0.249002                     
36                                          -0.249002                     
37                                          -0.249002                     
38                                          -0.249002                     
39                                          -0.249002                     
40                                          -0.249002                     
41                                          -0.249002                     
42                                          -0.249002                     
43                                          -0.249002                     
44                                          -0.249002                     
45                                          -0.249002                     
46                                          -0.249002                     
47                                          -0.249002                     
48                                          -0.249002                     
49                                          -0.249002                     

    Steel Plate Axial Ductility Damage Index Response Spectrum Fiber 01  
0                                           -0.017807                    
1                                           -0.017807                    
2                                           -0.017807                    
3                                           -0.017807                    
4                                           -0.017807                    
5                                           -0.017807                    
6                                           -0.017807                    
7                                           -0.017807                    
8                                           -0.017807                    
9                                           -0.017807                    
10                                          -0.017807                    
11                                          -0.017807                    
12                                          -0.017807                    
13                                          -0.017807                    
14                                          -0.017807                    
15                                          -0.017807                    
16                                          -0.017807                    
17                                          -0.017807                    
18                                          -0.017807                    
19                                          -0.017807                    
20                                          -0.017807                    
21                                          -0.017807                    
22                                          -0.017807                    
23                                          -0.017807                    
24                                          -0.017807                    
25                                          -0.017807                    
26                                          -0.017807                    
27                                          -0.017807                    
28                                          -0.017807                    
29                                          -0.017807                    
30                                          -0.017807                    
31                                          -0.017807                    
32                                          -0.017807                    
33                                          -0.017807                    
34                                          -0.017807                    
35                                          -0.017807                    
36                                          -0.017807                    
37                                          -0.017807                    
38                                          -0.017807                    
39                                          -0.017807                    
40                                          -0.017807                    
41                                          -0.017807                    
42                                          -0.017807                    
43                                          -0.017807                    
44                                          -0.017807                    
45                                          -0.017807                    
46                                          -0.017807                    
47                                          -0.017807                    
48                                          -0.017807                    
49                                          -0.017807

### Multiple Regression Model
def Multiple_Regression(df):
    import statsmodels.api as sm
    # Add a constant term for the intercept
    X = sm.add_constant(df[['Displacement Response Spectrum',
                            'Velocity Response Spectrum',
                            'Acceleration Response Spectrum',
                            'Base-shear Response Spectrum',
                            'Section Ductility Damage Index Response Spectrum',
                            'Concrete Axial Ductility Damage Index Response Spectrum Fiber 01',
                            'Steel Rebar Axial Ductility Damage Index Response Spectrum Fiber 01',
                            'Steel Plate Axial Ductility Damage Index Response Spectrum Fiber 01']])

    # Fit the multiple regression model
    model = sm.OLS(df['Structure Ductility Damage Index Response Spectrum'], X).fit()

    # Print the summary
    print(model.summary())

Multiple_Regression(df)

                                            OLS Regression Results                                            
==============================================================================================================
Dep. Variable:     Structure Ductility Damage Index Response Spectrum   R-squared:                       1.000
Model:                                                            OLS   Adj. R-squared:                  1.000
Method:                                                 Least Squares   F-statistic:                 3.037e+10
Date:                                                Tue, 01 Oct 2024   Prob (F-statistic):          1.23e-208
Time:                                                        09:43:03   Log-Likelihood:                 1119.8
No. Observations:                                                  50   AIC:                            -2228.
Df Residuals:                                                      44   BIC:                            -2216.
Df Model:                                                           5                                         
Covariance Type:                                            nonrobust                                         
=======================================================================================================================================
                                                                          coef    std err          t      P>|t|      [0.025      0.975]
---------------------------------------------------------------------------------------------------------------------------------------
const                                                                  -0.3901   8.34e-06  -4.68e+04      0.000      -0.390      -0.390
Displacement Response Spectrum                                          0.0085   2.39e-07   3.53e+04      0.000       0.008       0.008
Velocity Response Spectrum                                              0.0002      0.000      0.554      0.582      -0.000       0.001
Acceleration Response Spectrum                                      -6.374e-06   1.15e-05     -0.556      0.581   -2.95e-05    1.67e-05
Base-shear Response Spectrum                                         1.031e-12   1.23e-12      0.836      0.408   -1.46e-12    3.52e-12
Section Ductility Damage Index Response Spectrum                    -4.608e-05      0.000     -0.259      0.797      -0.000       0.000
Concrete Axial Ductility Damage Index Response Spectrum Fiber 01        0.0971   2.09e-06   4.64e+04      0.000       0.097       0.097
Steel Rebar Axial Ductility Damage Index Response Spectrum Fiber 01     0.0971   2.16e-06   4.51e+04      0.000       0.097       0.097
Steel Plate Axial Ductility Damage Index Response Spectrum Fiber 01     0.0070   3.53e-07   1.98e+04      0.000       0.007       0.007
==============================================================================
Omnibus:                        2.406   Durbin-Watson:                   0.765
Prob(Omnibus):                  0.300   Jarque-Bera (JB):                1.918
Skew:                          -0.329   Prob(JB):                        0.383
Kurtosis:                       2.302   Cond. No.                     2.55e+16
==============================================================================

Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
[2] The smallest eigenvalue is 3.48e-18. This might indicate that there are
strong multicollinearity problems or that the design matrix is singular.

# Run Lasso regression

import pandas as pd
import numpy as np
from sklearn.linear_model import Lasso
from sklearn.metrics import mean_squared_error
from sklearn.metrics import r2_score

import matplotlib.pyplot as plt
# Define the target variable and features
X = df.drop(columns=['Structure Ductility Damage Index Response Spectrum'])
y = df['Structure Ductility Damage Index Response Spectrum']

model = Lasso(alpha=0.05)
model.fit(X, y)

# Get the coefficients
coefficients = model.coef_
intercept = model.intercept_

# Predict the target variable
y_pred = model.predict(X)

# Calculate performance metrics
mse = mean_squared_error(y, y_pred)
r2 = r2_score(y, y_pred)

# Print the summary
print("Lasso Regression Summary")
print("------------------------")
print(f"Intercept: {intercept}")
print(f"Coefficients: {coefficients}")
print(f"Mean Squared Error: {mse}")
print(f"R-squared: {r2}")

# Plot the results
plt.figure(figsize=(10, 6))
plt.plot(y, label='True Values')
plt.plot(y_pred, label='Predicted Values', linestyle='--')
#plt.scatter(y,y_pred)
plt.xlabel('Sample Index')
plt.ylabel('Structure Ductility Damage Index Response Spectrum')
plt.title('Lasso Regression Results')
plt.legend()
plt.show()

Lasso Regression Summary
------------------------
Intercept: -0.2677501145835731
Coefficients: [0. 0. 0. 0. 0. 0. 0. 0.]
Mean Squared Error: 7.1099710403102694e-12
R-squared: 0.0

x = diC # Section Ductility Damage Index Response Spectrum element 50
y = diS # Structure Ductility Damage Index Response Spectrum
predicted_y = PREDICT_LSTM(x, y, look_back = 40, ITERATION = 5000)

# Plot the results
import matplotlib.pyplot as plt
plt.figure(figsize=(10, 6))
plt.scatter(x, y, color='blue', marker='+', label='DDI')
plt.scatter(0.004733, predicted_y, color='red', marker='o', label='Predicted next DDI')
plt.title(f'MACHINE LEARNING: LONG SHORT-TREM MEMERY (LSTM) METHOD - Predicted {predicted_y}')
plt.xlabel('Section Ductility Damage Index element 50')
plt.ylabel('Structure Ductility Damage Index')
plt.legend()
plt.grid()
plt.show()

Epoch 1/5000
10/10 - 3s - 254ms/step - loss: 0.0606
Epoch 2/5000
10/10 - 0s - 7ms/step - loss: 0.0385
Epoch 3/5000
10/10 - 0s - 9ms/step - loss: 0.0199
Epoch 4/5000
10/10 - 0s - 8ms/step - loss: 0.0067
Epoch 5/5000
10/10 - 0s - 9ms/step - loss: 6.8423e-04
Epoch 6/5000
10/10 - 0s - 9ms/step - loss: 2.8664e-04
Epoch 7/5000
10/10 - 0s - 8ms/step - loss: 2.9117e-04
Epoch 8/5000
10/10 - 0s - 8ms/step - loss: 1.8660e-05
Epoch 9/5000
10/10 - 0s - 7ms/step - loss: 2.2452e-05
Epoch 10/5000
10/10 - 0s - 8ms/step - loss: 1.1706e-05
Epoch 11/5000
10/10 - 0s - 9ms/step - loss: 5.8747e-07
Epoch 12/5000
10/10 - 0s - 9ms/step - loss: 1.5576e-06
Epoch 13/5000
10/10 - 0s - 9ms/step - loss: 2.4133e-07
Epoch 14/5000
10/10 - 0s - 8ms/step - loss: 1.0742e-07
Epoch 15/5000
10/10 - 0s - 9ms/step - loss: 6.0995e-08
Epoch 16/5000
10/10 - 0s - 7ms/step - loss: 5.5791e-09
Epoch 17/5000
10/10 - 0s - 8ms/step - loss: 9.1354e-09
Epoch 18/5000
10/10 - 0s - 10ms/step - loss: 5.5107e-10
Epoch 19/5000
10/10 - 0s - 8ms/step - loss: 1.1077e-09
Epoch 20/5000
10/10 - 0s - 9ms/step - loss: 9.9639e-11
Epoch 21/5000
10/10 - 0s - 22ms/step - loss: 1.2893e-10
Epoch 22/5000
10/10 - 0s - 17ms/step - loss: 1.8799e-11
Epoch 23/5000
10/10 - 0s - 8ms/step - loss: 1.5565e-11
Epoch 24/5000
10/10 - 0s - 8ms/step - loss: 2.8463e-12
Epoch 25/5000
10/10 - 0s - 11ms/step - loss: 2.1301e-12
Epoch 26/5000
10/10 - 0s - 8ms/step - loss: 6.1657e-13
Epoch 27/5000
10/10 - 0s - 9ms/step - loss: 5.4063e-13
Epoch 28/5000
10/10 - 0s - 8ms/step - loss: 3.4319e-13
Epoch 29/5000
10/10 - 0s - 7ms/step - loss: 3.5199e-13
Epoch 30/5000
10/10 - 0s - 8ms/step - loss: 3.6486e-13
Epoch 31/5000
10/10 - 0s - 18ms/step - loss: 3.2010e-13
Epoch 32/5000
10/10 - 0s - 9ms/step - loss: 3.9266e-13
Epoch 33/5000
10/10 - 0s - 8ms/step - loss: 3.3902e-13
Epoch 34/5000
10/10 - 0s - 9ms/step - loss: 3.4266e-13
Epoch 35/5000
10/10 - 0s - 9ms/step - loss: 3.5199e-13
Epoch 36/5000
10/10 - 0s - 6ms/step - loss: 3.3706e-13
Epoch 37/5000
10/10 - 0s - 23ms/step - loss: 3.2676e-13
Epoch 38/5000
10/10 - 0s - 9ms/step - loss: 3.5314e-13
Epoch 39/5000
10/10 - 0s - 9ms/step - loss: 3.4435e-13
Epoch 40/5000
10/10 - 0s - 9ms/step - loss: 3.7348e-13
Epoch 41/5000
10/10 - 0s - 7ms/step - loss: 3.3484e-13
Epoch 42/5000
10/10 - 0s - 9ms/step - loss: 3.7828e-13
Epoch 43/5000
10/10 - 0s - 8ms/step - loss: 3.2099e-13
Epoch 44/5000
10/10 - 0s - 8ms/step - loss: 3.5554e-13
Epoch 45/5000
10/10 - 0s - 9ms/step - loss: 3.6096e-13
Epoch 46/5000
10/10 - 0s - 9ms/step - loss: 3.3991e-13
Epoch 47/5000
10/10 - 0s - 10ms/step - loss: 3.4834e-13
Epoch 48/5000
10/10 - 0s - 8ms/step - loss: 3.5048e-13
Epoch 49/5000
10/10 - 0s - 9ms/step - loss: 3.9782e-13
Epoch 50/5000
10/10 - 0s - 9ms/step - loss: 3.6904e-13
Epoch 51/5000
10/10 - 0s - 9ms/step - loss: 3.5154e-13
Epoch 52/5000
10/10 - 0s - 10ms/step - loss: 3.5598e-13
Epoch 53/5000
10/10 - 0s - 9ms/step - loss: 3.4266e-13
Epoch 54/5000
10/10 - 0s - 7ms/step - loss: 3.4497e-13
Epoch 55/5000
10/10 - 0s - 8ms/step - loss: 4.2695e-13
Epoch 56/5000
10/10 - 0s - 8ms/step - loss: 3.3404e-13
Epoch 57/5000
10/10 - 0s - 8ms/step - loss: 4.3388e-13
Epoch 58/5000
10/10 - 0s - 7ms/step - loss: 3.6238e-13
Epoch 59/5000
10/10 - 0s - 7ms/step - loss: 3.6353e-13
Epoch 60/5000
10/10 - 0s - 8ms/step - loss: 3.5616e-13
Epoch 61/5000
10/10 - 0s - 8ms/step - loss: 3.6176e-13
Epoch 62/5000
10/10 - 0s - 8ms/step - loss: 3.5589e-13
Epoch 63/5000
10/10 - 0s - 7ms/step - loss: 3.6833e-13
Epoch 64/5000
10/10 - 0s - 8ms/step - loss: 3.4559e-13
Epoch 65/5000
10/10 - 0s - 10ms/step - loss: 3.5918e-13
Epoch 66/5000
10/10 - 0s - 8ms/step - loss: 4.6398e-13
Epoch 67/5000
10/10 - 0s - 7ms/step - loss: 3.6371e-13
Epoch 68/5000
10/10 - 0s - 7ms/step - loss: 4.0936e-13
Epoch 69/5000
10/10 - 0s - 9ms/step - loss: 3.7454e-13
Epoch 70/5000
10/10 - 0s - 10ms/step - loss: 3.3209e-13
Epoch 71/5000
10/10 - 0s - 18ms/step - loss: 4.0004e-13
Epoch 72/5000
10/10 - 0s - 9ms/step - loss: 5.1976e-13
Epoch 73/5000
10/10 - 0s - 8ms/step - loss: 2.9772e-13
Epoch 74/5000
10/10 - 0s - 8ms/step - loss: 3.9879e-13
Epoch 75/5000
10/10 - 0s - 8ms/step - loss: 3.8378e-13
Epoch 76/5000
10/10 - 0s - 9ms/step - loss: 4.4125e-13
Epoch 77/5000
10/10 - 0s - 8ms/step - loss: 3.5714e-13
Epoch 78/5000
10/10 - 0s - 8ms/step - loss: 3.9835e-13
Epoch 79/5000
10/10 - 0s - 7ms/step - loss: 4.6327e-13
Epoch 80/5000
10/10 - 0s - 8ms/step - loss: 3.4355e-13
Epoch 81/5000
10/10 - 0s - 7ms/step - loss: 4.1842e-13
Epoch 82/5000
10/10 - 0s - 8ms/step - loss: 3.9480e-13
Epoch 83/5000
10/10 - 0s - 9ms/step - loss: 3.6069e-13
Epoch 84/5000
10/10 - 0s - 10ms/step - loss: 3.5758e-13
Epoch 85/5000
10/10 - 0s - 9ms/step - loss: 4.6194e-13
Epoch 86/5000
10/10 - 0s - 15ms/step - loss: 2.9390e-13
Epoch 87/5000
10/10 - 0s - 17ms/step - loss: 3.7952e-13
Epoch 88/5000
10/10 - 0s - 9ms/step - loss: 5.6284e-13
Epoch 89/5000
10/10 - 0s - 9ms/step - loss: 3.7668e-13
Epoch 90/5000
10/10 - 0s - 10ms/step - loss: 4.1025e-13
Epoch 91/5000
10/10 - 0s - 7ms/step - loss: 3.7366e-13
Epoch 92/5000
10/10 - 0s - 8ms/step - loss: 3.7570e-13
Epoch 93/5000
10/10 - 0s - 7ms/step - loss: 3.8183e-13
Epoch 94/5000
10/10 - 0s - 6ms/step - loss: 3.8991e-13
Epoch 95/5000
10/10 - 0s - 7ms/step - loss: 3.6762e-13
Epoch 96/5000
10/10 - 0s - 6ms/step - loss: 5.1878e-13
Epoch 97/5000
10/10 - 0s - 7ms/step - loss: 4.8521e-13
Epoch 98/5000
10/10 - 0s - 8ms/step - loss: 4.7340e-13
Epoch 99/5000
10/10 - 0s - 9ms/step - loss: 3.2969e-13
Epoch 100/5000
10/10 - 0s - 9ms/step - loss: 4.7944e-13
Epoch 101/5000
10/10 - 0s - 9ms/step - loss: 3.8884e-13
Epoch 102/5000
10/10 - 0s - 9ms/step - loss: 3.7739e-13
Epoch 103/5000
10/10 - 0s - 9ms/step - loss: 4.6994e-13
Epoch 104/5000
10/10 - 0s - 9ms/step - loss: 3.8645e-13
Epoch 105/5000
10/10 - 0s - 9ms/step - loss: 4.0048e-13
Epoch 106/5000
10/10 - 0s - 8ms/step - loss: 3.5971e-13
Epoch 107/5000
10/10 - 0s - 11ms/step - loss: 3.6788e-13
Epoch 108/5000
10/10 - 0s - 11ms/step - loss: 3.7215e-13
Epoch 109/5000
10/10 - 0s - 9ms/step - loss: 3.6442e-13
Epoch 110/5000
10/10 - 0s - 10ms/step - loss: 4.6194e-13
Epoch 111/5000
10/10 - 0s - 20ms/step - loss: 4.0501e-13
Epoch 112/5000
10/10 - 0s - 10ms/step - loss: 4.7828e-13
Epoch 113/5000
10/10 - 0s - 8ms/step - loss: 5.4312e-13
Epoch 114/5000
10/10 - 0s - 15ms/step - loss: 7.9785e-13
Epoch 115/5000
10/10 - 0s - 14ms/step - loss: 5.2074e-13
Epoch 116/5000
10/10 - 0s - 15ms/step - loss: 4.8814e-13
Epoch 117/5000
10/10 - 0s - 20ms/step - loss: 3.4408e-13
Epoch 118/5000
10/10 - 0s - 18ms/step - loss: 4.4089e-13
Epoch 119/5000
10/10 - 0s - 18ms/step - loss: 5.5644e-13
Epoch 120/5000
10/10 - 0s - 18ms/step - loss: 5.9535e-13
Epoch 121/5000
10/10 - 0s - 10ms/step - loss: 4.3991e-13
Epoch 122/5000
10/10 - 0s - 21ms/step - loss: 3.9231e-13
Epoch 123/5000
10/10 - 0s - 9ms/step - loss: 4.2464e-13
Epoch 124/5000
10/10 - 0s - 14ms/step - loss: 3.8023e-13
Epoch 125/5000
10/10 - 0s - 15ms/step - loss: 4.5164e-13
Epoch 126/5000
10/10 - 0s - 9ms/step - loss: 3.6833e-13
Epoch 127/5000
10/10 - 0s - 16ms/step - loss: 3.9213e-13
Epoch 128/5000
10/10 - 0s - 15ms/step - loss: 4.8805e-13
Epoch 129/5000
10/10 - 0s - 13ms/step - loss: 2.9168e-13
Epoch 130/5000
10/10 - 0s - 11ms/step - loss: 4.7162e-13
Epoch 131/5000
10/10 - 0s - 11ms/step - loss: 4.1673e-13
Epoch 132/5000
10/10 - 0s - 14ms/step - loss: 3.7277e-13
Epoch 133/5000
10/10 - 0s - 15ms/step - loss: 4.0217e-13
Epoch 134/5000
10/10 - 0s - 18ms/step - loss: 5.8842e-13
Epoch 135/5000
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Epoch 140/5000
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Epoch 141/5000
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Epoch 142/5000
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Epoch 143/5000
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Epoch 144/5000
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Epoch 145/5000
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Epoch 146/5000
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Epoch 147/5000
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Epoch 148/5000
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Epoch 149/5000
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Epoch 151/5000
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Epoch 152/5000
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Epoch 153/5000
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Epoch 154/5000
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Epoch 155/5000
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Epoch 156/5000
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Epoch 157/5000
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Epoch 158/5000
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Epoch 159/5000
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Epoch 160/5000
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Epoch 161/5000
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Epoch 162/5000
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Epoch 163/5000
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Epoch 164/5000
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Epoch 165/5000
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Epoch 166/5000
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Epoch 167/5000
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Epoch 168/5000
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Epoch 169/5000
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Epoch 170/5000
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Epoch 171/5000
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Epoch 172/5000
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Epoch 173/5000
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Epoch 174/5000
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Epoch 175/5000
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Epoch 176/5000
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Epoch 177/5000
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Epoch 178/5000
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Epoch 179/5000
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Epoch 180/5000
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Epoch 181/5000
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Epoch 182/5000
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Epoch 183/5000
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Epoch 184/5000
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Epoch 185/5000
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Epoch 186/5000
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Epoch 187/5000
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Epoch 188/5000
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Epoch 189/5000
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Epoch 190/5000
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Epoch 191/5000
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Epoch 192/5000
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Epoch 193/5000
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Epoch 194/5000
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Epoch 195/5000
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Epoch 196/5000
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Epoch 197/5000
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Epoch 198/5000
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Epoch 199/5000
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Epoch 200/5000
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Epoch 201/5000
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Epoch 202/5000
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Epoch 203/5000
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Epoch 204/5000
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Epoch 205/5000
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Epoch 206/5000
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Epoch 207/5000
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Epoch 208/5000
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Epoch 209/5000
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Epoch 210/5000
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Epoch 211/5000
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Epoch 212/5000
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Epoch 213/5000
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Epoch 214/5000
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Epoch 215/5000
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Epoch 216/5000
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Epoch 217/5000
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Epoch 218/5000
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Epoch 219/5000
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Epoch 220/5000
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Epoch 221/5000
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Epoch 222/5000
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Epoch 223/5000
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Epoch 224/5000
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Epoch 225/5000
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Epoch 226/5000
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Epoch 227/5000
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Epoch 228/5000
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Epoch 229/5000
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Epoch 230/5000
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Epoch 231/5000
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Epoch 232/5000
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Epoch 233/5000
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Epoch 234/5000
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Epoch 235/5000
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Epoch 236/5000
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Epoch 237/5000
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Epoch 238/5000
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Epoch 239/5000
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Epoch 240/5000
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Epoch 241/5000
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Epoch 242/5000
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Epoch 243/5000
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Epoch 244/5000
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Epoch 245/5000
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Epoch 246/5000
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Epoch 247/5000
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Epoch 248/5000
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Epoch 249/5000
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Epoch 250/5000
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Epoch 251/5000
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Epoch 252/5000
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Epoch 253/5000
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Epoch 254/5000
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Epoch 255/5000
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Epoch 256/5000
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Epoch 257/5000
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Epoch 258/5000
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Epoch 259/5000
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Epoch 260/5000
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Epoch 261/5000
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Epoch 262/5000
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Epoch 263/5000
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Epoch 264/5000
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Epoch 265/5000
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Epoch 266/5000
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Epoch 267/5000
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Epoch 268/5000
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Epoch 269/5000
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Epoch 270/5000
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Epoch 271/5000
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Epoch 272/5000
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Epoch 273/5000
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Epoch 274/5000
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Epoch 275/5000
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Epoch 276/5000
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Epoch 277/5000
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Epoch 278/5000
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Epoch 279/5000
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Epoch 280/5000
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Epoch 281/5000
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Epoch 282/5000
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Epoch 283/5000
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Epoch 284/5000
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Epoch 285/5000
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Epoch 286/5000
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Epoch 287/5000
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Epoch 288/5000
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Epoch 289/5000
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Epoch 290/5000
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Epoch 291/5000
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Epoch 292/5000
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Epoch 293/5000
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Epoch 294/5000
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Epoch 295/5000
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Epoch 296/5000
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Epoch 297/5000
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Epoch 298/5000
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Epoch 299/5000
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Epoch 300/5000
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Epoch 301/5000
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Epoch 302/5000
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Epoch 303/5000
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Epoch 304/5000
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Epoch 305/5000
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Epoch 306/5000
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Epoch 307/5000
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Epoch 308/5000
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Epoch 309/5000
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Epoch 310/5000
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Epoch 311/5000
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Epoch 312/5000
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Epoch 313/5000
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Epoch 314/5000
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Epoch 315/5000
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Epoch 316/5000
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Epoch 317/5000
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Epoch 318/5000
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Epoch 319/5000
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Epoch 320/5000
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Epoch 321/5000
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Epoch 322/5000
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Epoch 323/5000
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Epoch 324/5000
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Epoch 325/5000
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Epoch 326/5000
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Epoch 327/5000
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Epoch 328/5000
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Epoch 329/5000
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Epoch 330/5000
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Epoch 331/5000
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Epoch 332/5000
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Epoch 333/5000
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Epoch 334/5000
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Epoch 335/5000
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Epoch 336/5000
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Epoch 337/5000
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Epoch 338/5000
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Epoch 339/5000
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Epoch 340/5000
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Epoch 341/5000
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Epoch 342/5000
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Epoch 343/5000
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Epoch 344/5000
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Epoch 345/5000
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Epoch 346/5000
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Epoch 347/5000
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Epoch 348/5000
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Epoch 349/5000
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Epoch 350/5000
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Epoch 351/5000
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Epoch 352/5000
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Epoch 353/5000
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Epoch 354/5000
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Epoch 355/5000
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Epoch 356/5000
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Epoch 357/5000
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Epoch 358/5000
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Epoch 359/5000
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Epoch 360/5000
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Epoch 361/5000
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Epoch 362/5000
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Epoch 363/5000
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Epoch 364/5000
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Epoch 365/5000
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Epoch 366/5000
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Epoch 367/5000
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Epoch 368/5000
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Epoch 369/5000
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Epoch 370/5000
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Epoch 371/5000
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Epoch 372/5000
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Epoch 373/5000
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Epoch 374/5000
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Epoch 375/5000
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Epoch 376/5000
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Epoch 377/5000
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Epoch 378/5000
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Epoch 379/5000
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Epoch 380/5000
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Epoch 381/5000
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Epoch 382/5000
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Epoch 383/5000
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Epoch 384/5000
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Epoch 385/5000
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Epoch 386/5000
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Epoch 387/5000
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Epoch 388/5000
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Epoch 389/5000
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Epoch 390/5000
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Epoch 391/5000
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Epoch 392/5000
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Epoch 393/5000
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Epoch 394/5000
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Epoch 395/5000
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Epoch 396/5000
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Epoch 397/5000
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Epoch 398/5000
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Epoch 399/5000
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Epoch 400/5000
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Epoch 401/5000
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Epoch 402/5000
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Epoch 403/5000
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Epoch 404/5000
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Epoch 405/5000
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Epoch 406/5000
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Epoch 407/5000
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Epoch 408/5000
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Epoch 409/5000
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Epoch 410/5000
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Epoch 411/5000
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Epoch 412/5000
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Epoch 413/5000
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Epoch 414/5000
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Epoch 415/5000
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Epoch 416/5000
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Epoch 417/5000
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Epoch 418/5000
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Epoch 419/5000
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Epoch 420/5000
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Epoch 421/5000
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Epoch 422/5000
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Epoch 423/5000
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Epoch 424/5000
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Epoch 425/5000
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Epoch 426/5000
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Epoch 427/5000
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Epoch 428/5000
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Epoch 429/5000
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Epoch 430/5000
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Epoch 431/5000
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Epoch 432/5000
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Epoch 433/5000
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Epoch 434/5000
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Epoch 435/5000
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Epoch 436/5000
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Epoch 437/5000
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Epoch 438/5000
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Epoch 439/5000
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Epoch 440/5000
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Epoch 441/5000
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Epoch 442/5000
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Epoch 443/5000
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Epoch 444/5000
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Epoch 445/5000
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Epoch 446/5000
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Epoch 447/5000
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Epoch 448/5000
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Epoch 449/5000
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Epoch 450/5000
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Epoch 451/5000
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Epoch 452/5000
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Epoch 453/5000
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Epoch 454/5000
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Epoch 455/5000
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Epoch 456/5000
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Epoch 457/5000
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Epoch 458/5000
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Epoch 459/5000
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Epoch 460/5000
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Epoch 461/5000
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Epoch 462/5000
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Epoch 463/5000
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Epoch 464/5000
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Epoch 465/5000
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Epoch 466/5000
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Epoch 467/5000
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Epoch 468/5000
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Epoch 469/5000
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Epoch 470/5000
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Epoch 471/5000
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Epoch 472/5000
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Epoch 473/5000
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Epoch 474/5000
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Epoch 475/5000
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Epoch 476/5000
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Epoch 477/5000
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Epoch 478/5000
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Epoch 479/5000
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Epoch 480/5000
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Epoch 481/5000
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Epoch 482/5000
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Epoch 483/5000
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Epoch 484/5000
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Epoch 485/5000
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Epoch 486/5000
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Epoch 487/5000
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Epoch 488/5000
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Epoch 489/5000
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Epoch 490/5000
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Epoch 491/5000
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Epoch 492/5000
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Epoch 493/5000
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Epoch 494/5000
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Epoch 495/5000
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Epoch 496/5000
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Epoch 497/5000
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Epoch 498/5000
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Epoch 499/5000
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Epoch 500/5000
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Epoch 501/5000
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Epoch 502/5000
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Epoch 503/5000
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Epoch 504/5000
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Epoch 505/5000
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Epoch 506/5000
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Epoch 507/5000
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Epoch 508/5000
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Epoch 509/5000
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Epoch 510/5000
10/10 - 0s - 10ms/step - loss: 9.1500e-13
Epoch 511/5000
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Epoch 512/5000
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Epoch 513/5000
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Epoch 514/5000
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Epoch 515/5000
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Epoch 516/5000
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Epoch 517/5000
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Epoch 518/5000
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Epoch 519/5000
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Epoch 520/5000
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Epoch 521/5000
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Epoch 522/5000
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Epoch 523/5000
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Epoch 524/5000
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Epoch 525/5000
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Epoch 526/5000
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Epoch 527/5000
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Epoch 528/5000
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Epoch 529/5000
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Epoch 530/5000
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Epoch 531/5000
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Epoch 532/5000
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Epoch 533/5000
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Epoch 534/5000
10/10 - 0s - 7ms/step - loss: 6.0814e-12
Epoch 535/5000
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Epoch 536/5000
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Epoch 537/5000
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Epoch 538/5000
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Epoch 539/5000
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Epoch 540/5000
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Epoch 541/5000
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Epoch 542/5000
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Epoch 543/5000
10/10 - 0s - 11ms/step - loss: 9.1394e-13
Epoch 544/5000
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Epoch 545/5000
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Epoch 546/5000
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Epoch 547/5000
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Epoch 548/5000
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Epoch 549/5000
10/10 - 0s - 10ms/step - loss: 8.0531e-13
Epoch 550/5000
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Epoch 551/5000
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Epoch 552/5000
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Epoch 553/5000
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Epoch 554/5000
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Epoch 555/5000
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Epoch 556/5000
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Epoch 557/5000
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Epoch 558/5000
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Epoch 559/5000
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Epoch 560/5000
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Epoch 561/5000
10/10 - 0s - 9ms/step - loss: 6.7605e-12
Epoch 562/5000
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Epoch 563/5000
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Epoch 564/5000
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Epoch 565/5000
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Epoch 566/5000
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Epoch 567/5000
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Epoch 568/5000
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Epoch 569/5000
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Epoch 570/5000
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Epoch 571/5000
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Epoch 572/5000
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Epoch 573/5000
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Epoch 574/5000
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Epoch 575/5000
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Epoch 576/5000
10/10 - 0s - 10ms/step - loss: 3.0737e-12
Epoch 577/5000
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Epoch 578/5000
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Epoch 579/5000
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Epoch 580/5000
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Epoch 581/5000
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Epoch 582/5000
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Epoch 583/5000
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Epoch 584/5000
10/10 - 0s - 10ms/step - loss: 6.6747e-13
Epoch 585/5000
10/10 - 0s - 8ms/step - loss: 2.1106e-12
Epoch 586/5000
10/10 - 0s - 8ms/step - loss: 2.8463e-12
Epoch 587/5000
10/10 - 0s - 9ms/step - loss: 2.6882e-12
Epoch 588/5000
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Epoch 589/5000
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Epoch 590/5000
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Epoch 591/5000
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Epoch 592/5000
10/10 - 0s - 10ms/step - loss: 9.9645e-13
Epoch 593/5000
10/10 - 0s - 10ms/step - loss: 8.8383e-13
Epoch 594/5000
10/10 - 0s - 10ms/step - loss: 1.0982e-12
Epoch 595/5000
10/10 - 0s - 10ms/step - loss: 6.6844e-13
Epoch 596/5000
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Epoch 597/5000
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Epoch 598/5000
10/10 - 0s - 8ms/step - loss: 9.8073e-13
Epoch 599/5000
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Epoch 600/5000
10/10 - 0s - 8ms/step - loss: 7.5501e-12
Epoch 601/5000
10/10 - 0s - 8ms/step - loss: 1.0729e-11
Epoch 602/5000
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Epoch 603/5000
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Epoch 604/5000
10/10 - 0s - 11ms/step - loss: 6.9580e-13
Epoch 605/5000
10/10 - 0s - 9ms/step - loss: 9.9920e-13
Epoch 606/5000
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Epoch 607/5000
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Epoch 608/5000
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Epoch 609/5000
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Epoch 610/5000
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Epoch 611/5000
10/10 - 0s - 9ms/step - loss: 1.9549e-12
Epoch 612/5000
10/10 - 0s - 7ms/step - loss: 2.0619e-12
Epoch 613/5000
10/10 - 0s - 8ms/step - loss: 3.5981e-12
Epoch 614/5000
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Epoch 615/5000
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Epoch 616/5000
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Epoch 617/5000
10/10 - 0s - 9ms/step - loss: 1.3786e-12
Epoch 618/5000
10/10 - 0s - 8ms/step - loss: 1.2649e-12
Epoch 619/5000
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Epoch 620/5000
10/10 - 0s - 8ms/step - loss: 7.8479e-13
Epoch 621/5000
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Epoch 622/5000
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Epoch 623/5000
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Epoch 624/5000
10/10 - 0s - 7ms/step - loss: 3.2105e-12
Epoch 625/5000
10/10 - 0s - 6ms/step - loss: 4.5305e-12
Epoch 626/5000
10/10 - 0s - 9ms/step - loss: 1.1843e-11
Epoch 627/5000
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Epoch 628/5000
10/10 - 0s - 11ms/step - loss: 1.1393e-11
Epoch 629/5000
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Epoch 630/5000
10/10 - 0s - 7ms/step - loss: 1.2440e-11
Epoch 631/5000
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Epoch 632/5000
10/10 - 0s - 9ms/step - loss: 8.6758e-12
Epoch 633/5000
10/10 - 0s - 10ms/step - loss: 1.0339e-11
Epoch 634/5000
10/10 - 0s - 11ms/step - loss: 8.2695e-12
Epoch 635/5000
10/10 - 0s - 9ms/step - loss: 1.2403e-12
Epoch 636/5000
10/10 - 0s - 7ms/step - loss: 4.4365e-12
Epoch 637/5000
10/10 - 0s - 8ms/step - loss: 3.8197e-12
Epoch 638/5000
10/10 - 0s - 7ms/step - loss: 2.9023e-12
Epoch 639/5000
10/10 - 0s - 10ms/step - loss: 1.6185e-12
Epoch 640/5000
10/10 - 0s - 12ms/step - loss: 8.9001e-12
Epoch 641/5000
10/10 - 0s - 11ms/step - loss: 7.1602e-12
Epoch 642/5000
10/10 - 0s - 9ms/step - loss: 2.3591e-12
Epoch 643/5000
10/10 - 0s - 6ms/step - loss: 9.2166e-13
Epoch 644/5000
10/10 - 0s - 9ms/step - loss: 3.2442e-12
Epoch 645/5000
10/10 - 0s - 7ms/step - loss: 5.8344e-12
Epoch 646/5000
10/10 - 0s - 9ms/step - loss: 3.6779e-12
Epoch 647/5000
10/10 - 0s - 11ms/step - loss: 5.1783e-12
Epoch 648/5000
10/10 - 0s - 9ms/step - loss: 1.6657e-12
Epoch 649/5000
10/10 - 0s - 10ms/step - loss: 3.3812e-12
Epoch 650/5000
10/10 - 0s - 8ms/step - loss: 2.7459e-12
Epoch 651/5000
10/10 - 0s - 11ms/step - loss: 2.1054e-12
Epoch 652/5000
10/10 - 0s - 10ms/step - loss: 5.1180e-12
Epoch 653/5000
10/10 - 0s - 10ms/step - loss: 8.3831e-12
Epoch 654/5000
10/10 - 0s - 7ms/step - loss: 8.8596e-12
Epoch 655/5000
10/10 - 0s - 8ms/step - loss: 2.5000e-12
Epoch 656/5000
10/10 - 0s - 8ms/step - loss: 4.5701e-12
Epoch 657/5000
10/10 - 0s - 10ms/step - loss: 5.8090e-12
Epoch 658/5000
10/10 - 0s - 11ms/step - loss: 1.0370e-11
Epoch 659/5000
10/10 - 0s - 8ms/step - loss: 2.6026e-12
Epoch 660/5000
10/10 - 0s - 6ms/step - loss: 1.0993e-12
Epoch 661/5000
10/10 - 0s - 8ms/step - loss: 1.5374e-12
Epoch 662/5000
10/10 - 0s - 9ms/step - loss: 1.3826e-12
Epoch 663/5000
10/10 - 0s - 11ms/step - loss: 6.9278e-13
Epoch 664/5000
10/10 - 0s - 11ms/step - loss: 1.6020e-12
Epoch 665/5000
10/10 - 0s - 9ms/step - loss: 7.4634e-13
Epoch 666/5000
10/10 - 0s - 7ms/step - loss: 1.4642e-12
Epoch 667/5000
10/10 - 0s - 7ms/step - loss: 1.6667e-12
Epoch 668/5000
10/10 - 0s - 7ms/step - loss: 1.4774e-12
Epoch 669/5000
10/10 - 0s - 11ms/step - loss: 4.2160e-12
Epoch 670/5000
10/10 - 0s - 10ms/step - loss: 1.7848e-12
Epoch 671/5000
10/10 - 0s - 10ms/step - loss: 1.0081e-12
Epoch 672/5000
10/10 - 0s - 9ms/step - loss: 1.3148e-12
Epoch 673/5000
10/10 - 0s - 10ms/step - loss: 1.8034e-12
Epoch 674/5000
10/10 - 0s - 10ms/step - loss: 6.3324e-12
Epoch 675/5000
10/10 - 0s - 11ms/step - loss: 4.3371e-12
Epoch 676/5000
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Epoch 677/5000
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Epoch 678/5000
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Epoch 679/5000
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Epoch 680/5000
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Epoch 681/5000
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Epoch 682/5000
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Epoch 683/5000
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Epoch 684/5000
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Epoch 685/5000
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Epoch 686/5000
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Epoch 687/5000
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Epoch 688/5000
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Epoch 689/5000
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Epoch 690/5000
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Epoch 691/5000
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Epoch 692/5000
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Epoch 693/5000
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Epoch 694/5000
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Epoch 695/5000
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Epoch 696/5000
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Epoch 697/5000
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Epoch 698/5000
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Epoch 699/5000
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Epoch 700/5000
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Epoch 701/5000
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Epoch 702/5000
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Epoch 703/5000
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Epoch 704/5000
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Epoch 705/5000
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Epoch 706/5000
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Epoch 707/5000
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Epoch 708/5000
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Epoch 709/5000
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Epoch 710/5000
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Epoch 711/5000
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Epoch 712/5000
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Epoch 713/5000
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Epoch 714/5000
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Epoch 715/5000
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Epoch 716/5000
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Epoch 717/5000
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Epoch 718/5000
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Epoch 719/5000
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Epoch 720/5000
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Epoch 721/5000
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Epoch 722/5000
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Epoch 723/5000
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Epoch 724/5000
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Epoch 725/5000
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Epoch 726/5000
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Epoch 727/5000
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Epoch 728/5000
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Epoch 729/5000
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Epoch 730/5000
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Epoch 731/5000
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Epoch 732/5000
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Epoch 733/5000
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Epoch 734/5000
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Epoch 735/5000
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Epoch 736/5000
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Epoch 737/5000
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Epoch 738/5000
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Epoch 739/5000
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Epoch 740/5000
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Epoch 741/5000
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Epoch 742/5000
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Epoch 743/5000
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Epoch 744/5000
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Epoch 745/5000
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Epoch 746/5000
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Epoch 747/5000
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Epoch 748/5000
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Epoch 749/5000
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Epoch 750/5000
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Epoch 751/5000
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Epoch 752/5000
10/10 - 0s - 9ms/step - loss: 9.2740e-12
Epoch 753/5000
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Epoch 754/5000
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Epoch 755/5000
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Epoch 756/5000
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Epoch 757/5000
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Epoch 758/5000
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Epoch 759/5000
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Epoch 760/5000
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Epoch 761/5000
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Epoch 762/5000
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Epoch 763/5000
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Epoch 764/5000
10/10 - 0s - 9ms/step - loss: 9.4138e-13
Epoch 765/5000
10/10 - 0s - 8ms/step - loss: 4.4405e-12
Epoch 766/5000
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Epoch 767/5000
10/10 - 0s - 8ms/step - loss: 1.3198e-11
Epoch 768/5000
10/10 - 0s - 8ms/step - loss: 1.6236e-11
Epoch 769/5000
10/10 - 0s - 9ms/step - loss: 1.2839e-11
Epoch 770/5000
10/10 - 0s - 9ms/step - loss: 6.7438e-12
Epoch 771/5000
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Epoch 772/5000
10/10 - 0s - 9ms/step - loss: 5.3311e-12
Epoch 773/5000
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Epoch 774/5000
10/10 - 0s - 9ms/step - loss: 1.7636e-11
Epoch 775/5000
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Epoch 776/5000
10/10 - 0s - 8ms/step - loss: 2.8094e-12
Epoch 777/5000
10/10 - 0s - 8ms/step - loss: 1.3343e-11
Epoch 778/5000
10/10 - 0s - 9ms/step - loss: 1.6465e-11
Epoch 779/5000
10/10 - 0s - 9ms/step - loss: 9.3185e-12
Epoch 780/5000
10/10 - 0s - 9ms/step - loss: 2.5392e-12
Epoch 781/5000
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Epoch 782/5000
10/10 - 0s - 8ms/step - loss: 7.6376e-12
Epoch 783/5000
10/10 - 0s - 10ms/step - loss: 8.0897e-12
Epoch 784/5000
10/10 - 0s - 9ms/step - loss: 7.6325e-12
Epoch 785/5000
10/10 - 0s - 8ms/step - loss: 1.9653e-11
Epoch 786/5000
10/10 - 0s - 8ms/step - loss: 9.4269e-12
Epoch 787/5000
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Epoch 788/5000
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Epoch 789/5000
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Epoch 790/5000
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Epoch 791/5000
10/10 - 0s - 8ms/step - loss: 3.0469e-11
Epoch 792/5000
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Epoch 793/5000
10/10 - 0s - 8ms/step - loss: 6.3929e-11
Epoch 794/5000
10/10 - 0s - 9ms/step - loss: 6.2651e-11
Epoch 795/5000
10/10 - 0s - 9ms/step - loss: 6.7956e-11
Epoch 796/5000
10/10 - 0s - 9ms/step - loss: 3.1046e-11
Epoch 797/5000
10/10 - 0s - 7ms/step - loss: 1.1648e-11
Epoch 798/5000
10/10 - 0s - 8ms/step - loss: 1.1167e-11
Epoch 799/5000
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Epoch 800/5000
10/10 - 0s - 9ms/step - loss: 7.6158e-12
Epoch 801/5000
10/10 - 0s - 8ms/step - loss: 6.2466e-12
Epoch 802/5000
10/10 - 0s - 9ms/step - loss: 2.6843e-11
Epoch 803/5000
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Epoch 804/5000
10/10 - 0s - 10ms/step - loss: 8.2609e-12
Epoch 805/5000
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Epoch 806/5000
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Epoch 807/5000
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Epoch 808/5000
10/10 - 0s - 11ms/step - loss: 2.6212e-11
Epoch 809/5000
10/10 - 0s - 10ms/step - loss: 1.8226e-11
Epoch 810/5000
10/10 - 0s - 9ms/step - loss: 5.8034e-12
Epoch 811/5000
10/10 - 0s - 9ms/step - loss: 1.3038e-11
Epoch 812/5000
10/10 - 0s - 9ms/step - loss: 7.9717e-12
Epoch 813/5000
10/10 - 0s - 8ms/step - loss: 3.3716e-11
Epoch 814/5000
10/10 - 0s - 8ms/step - loss: 7.4004e-11
Epoch 815/5000
10/10 - 0s - 8ms/step - loss: 4.9531e-11
Epoch 816/5000
10/10 - 0s - 9ms/step - loss: 1.5883e-11
Epoch 817/5000
10/10 - 0s - 9ms/step - loss: 1.1737e-11
Epoch 818/5000
10/10 - 0s - 9ms/step - loss: 8.8719e-12
Epoch 819/5000
10/10 - 0s - 9ms/step - loss: 1.6674e-11
Epoch 820/5000
10/10 - 0s - 8ms/step - loss: 2.2507e-11
Epoch 821/5000
10/10 - 0s - 9ms/step - loss: 1.6825e-11
Epoch 822/5000
10/10 - 0s - 8ms/step - loss: 4.4492e-12
Epoch 823/5000
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Epoch 824/5000
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Epoch 825/5000
10/10 - 0s - 8ms/step - loss: 3.3550e-12
Epoch 826/5000
10/10 - 0s - 8ms/step - loss: 4.9039e-12
Epoch 827/5000
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Epoch 828/5000
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Epoch 829/5000
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Epoch 830/5000
10/10 - 0s - 9ms/step - loss: 9.0760e-12
Epoch 831/5000
10/10 - 0s - 8ms/step - loss: 2.5023e-11
Epoch 832/5000
10/10 - 0s - 8ms/step - loss: 2.5145e-11
Epoch 833/5000
10/10 - 0s - 9ms/step - loss: 6.8114e-12
Epoch 834/5000
10/10 - 0s - 10ms/step - loss: 2.1288e-11
Epoch 835/5000
10/10 - 0s - 10ms/step - loss: 2.0303e-11
Epoch 836/5000
10/10 - 0s - 7ms/step - loss: 2.6550e-11
Epoch 837/5000
10/10 - 0s - 8ms/step - loss: 3.8995e-11
Epoch 838/5000
10/10 - 0s - 10ms/step - loss: 3.7302e-11
Epoch 839/5000
10/10 - 0s - 8ms/step - loss: 1.0854e-11
Epoch 840/5000
10/10 - 0s - 9ms/step - loss: 1.0840e-11
Epoch 841/5000
10/10 - 0s - 8ms/step - loss: 1.1521e-11
Epoch 842/5000
10/10 - 0s - 8ms/step - loss: 1.6230e-11
Epoch 843/5000
10/10 - 0s - 8ms/step - loss: 6.3425e-11
Epoch 844/5000
10/10 - 0s - 9ms/step - loss: 7.9948e-11
Epoch 845/5000
10/10 - 0s - 9ms/step - loss: 3.0756e-11
Epoch 846/5000
10/10 - 0s - 9ms/step - loss: 3.3421e-11
Epoch 847/5000
10/10 - 0s - 8ms/step - loss: 1.4301e-11
Epoch 848/5000
10/10 - 0s - 9ms/step - loss: 5.1805e-11
Epoch 849/5000
10/10 - 0s - 8ms/step - loss: 7.0504e-11
Epoch 850/5000
10/10 - 0s - 8ms/step - loss: 6.9160e-11
Epoch 851/5000
10/10 - 0s - 8ms/step - loss: 1.9762e-11
Epoch 852/5000
10/10 - 0s - 10ms/step - loss: 2.2224e-11
Epoch 853/5000
10/10 - 0s - 9ms/step - loss: 1.3389e-11
Epoch 854/5000
10/10 - 0s - 8ms/step - loss: 1.1639e-10
Epoch 855/5000
10/10 - 0s - 9ms/step - loss: 1.1863e-11
Epoch 856/5000
10/10 - 0s - 9ms/step - loss: 4.6227e-11
Epoch 857/5000
10/10 - 0s - 9ms/step - loss: 1.0162e-10
Epoch 858/5000
10/10 - 0s - 10ms/step - loss: 1.9371e-11
Epoch 859/5000
10/10 - 0s - 8ms/step - loss: 3.7303e-11
Epoch 860/5000
10/10 - 0s - 7ms/step - loss: 1.6905e-10
Epoch 861/5000
10/10 - 0s - 8ms/step - loss: 2.2423e-10
Epoch 862/5000
10/10 - 0s - 10ms/step - loss: 4.2061e-10
Epoch 863/5000
10/10 - 0s - 9ms/step - loss: 2.3261e-10
Epoch 864/5000
10/10 - 0s - 11ms/step - loss: 9.6428e-10
Epoch 865/5000
10/10 - 0s - 9ms/step - loss: 6.5284e-10
Epoch 866/5000
10/10 - 0s - 9ms/step - loss: 4.5152e-10
Epoch 867/5000
10/10 - 0s - 8ms/step - loss: 5.8647e-11
Epoch 868/5000
10/10 - 0s - 10ms/step - loss: 2.3602e-10
Epoch 869/5000
10/10 - 0s - 9ms/step - loss: 1.0727e-10
Epoch 870/5000
10/10 - 0s - 8ms/step - loss: 5.1605e-10
Epoch 871/5000
10/10 - 0s - 10ms/step - loss: 1.2951e-08
Epoch 872/5000
10/10 - 0s - 9ms/step - loss: 2.3107e-07
Epoch 873/5000
10/10 - 0s - 9ms/step - loss: 8.5281e-08
Epoch 874/5000
10/10 - 0s - 12ms/step - loss: 2.3543e-08
Epoch 875/5000
10/10 - 0s - 17ms/step - loss: 1.0559e-08
Epoch 876/5000
10/10 - 0s - 16ms/step - loss: 4.7064e-09
Epoch 877/5000
10/10 - 0s - 15ms/step - loss: 2.5196e-09
Epoch 878/5000
10/10 - 0s - 8ms/step - loss: 2.0886e-09
Epoch 879/5000
10/10 - 0s - 9ms/step - loss: 1.2919e-09
Epoch 880/5000
10/10 - 0s - 8ms/step - loss: 1.2121e-09
Epoch 881/5000
10/10 - 0s - 9ms/step - loss: 2.2690e-10
Epoch 882/5000
10/10 - 0s - 9ms/step - loss: 1.4111e-10
Epoch 883/5000
10/10 - 0s - 14ms/step - loss: 9.4230e-11
Epoch 884/5000
10/10 - 0s - 18ms/step - loss: 3.7585e-09
Epoch 885/5000
10/10 - 0s - 8ms/step - loss: 4.6382e-08
Epoch 886/5000
10/10 - 0s - 9ms/step - loss: 1.8070e-07
Epoch 887/5000
10/10 - 0s - 7ms/step - loss: 3.6275e-08
Epoch 888/5000
10/10 - 0s - 9ms/step - loss: 1.2764e-08
Epoch 889/5000
10/10 - 0s - 9ms/step - loss: 5.3509e-09
Epoch 890/5000
10/10 - 0s - 9ms/step - loss: 3.3517e-09
Epoch 891/5000
10/10 - 0s - 8ms/step - loss: 5.0996e-10
Epoch 892/5000
10/10 - 0s - 8ms/step - loss: 9.2214e-10
Epoch 893/5000
10/10 - 0s - 7ms/step - loss: 1.0285e-08
Epoch 894/5000
10/10 - 0s - 8ms/step - loss: 3.1709e-08
Epoch 895/5000
10/10 - 0s - 7ms/step - loss: 6.5783e-08
Epoch 896/5000
10/10 - 0s - 8ms/step - loss: 3.0617e-08
Epoch 897/5000
10/10 - 0s - 9ms/step - loss: 6.3733e-09
Epoch 898/5000
10/10 - 0s - 8ms/step - loss: 3.0586e-08
Epoch 899/5000
10/10 - 0s - 7ms/step - loss: 4.4928e-08
Epoch 900/5000
10/10 - 0s - 10ms/step - loss: 4.4963e-08
Epoch 901/5000
10/10 - 0s - 8ms/step - loss: 1.7453e-08
Epoch 902/5000
10/10 - 0s - 9ms/step - loss: 8.8586e-10
Epoch 903/5000
10/10 - 0s - 8ms/step - loss: 3.6968e-09
Epoch 904/5000
10/10 - 0s - 8ms/step - loss: 1.5672e-08
Epoch 905/5000
10/10 - 0s - 8ms/step - loss: 2.3265e-07
Epoch 906/5000
10/10 - 0s - 9ms/step - loss: 1.2174e-07
Epoch 907/5000
10/10 - 0s - 9ms/step - loss: 4.3396e-08
Epoch 908/5000
10/10 - 0s - 8ms/step - loss: 1.3211e-08
Epoch 909/5000
10/10 - 0s - 8ms/step - loss: 5.3803e-09
Epoch 910/5000
10/10 - 0s - 23ms/step - loss: 2.8985e-09
Epoch 911/5000
10/10 - 0s - 9ms/step - loss: 9.4303e-10
Epoch 912/5000
10/10 - 0s - 8ms/step - loss: 9.3255e-10
Epoch 913/5000
10/10 - 0s - 8ms/step - loss: 2.4117e-09
Epoch 914/5000
10/10 - 0s - 8ms/step - loss: 1.7846e-09
Epoch 915/5000
10/10 - 0s - 8ms/step - loss: 1.1382e-08
Epoch 916/5000
10/10 - 0s - 9ms/step - loss: 4.8712e-08
Epoch 917/5000
10/10 - 0s - 7ms/step - loss: 1.1103e-07
Epoch 918/5000
10/10 - 0s - 9ms/step - loss: 1.7398e-08
Epoch 919/5000
10/10 - 0s - 9ms/step - loss: 2.4777e-08
Epoch 920/5000
10/10 - 0s - 7ms/step - loss: 5.0970e-09
Epoch 921/5000
10/10 - 0s - 9ms/step - loss: 1.4110e-09
Epoch 922/5000
10/10 - 0s - 12ms/step - loss: 4.5181e-09
Epoch 923/5000
10/10 - 0s - 11ms/step - loss: 4.6507e-08
Epoch 924/5000
10/10 - 0s - 9ms/step - loss: 3.1373e-07
Epoch 925/5000
10/10 - 0s - 9ms/step - loss: 7.8174e-08
Epoch 926/5000
10/10 - 0s - 8ms/step - loss: 3.0653e-08
Epoch 927/5000
10/10 - 0s - 8ms/step - loss: 1.1292e-08
Epoch 928/5000
10/10 - 0s - 8ms/step - loss: 6.1378e-09
Epoch 929/5000
10/10 - 0s - 8ms/step - loss: 3.4674e-09
Epoch 930/5000
10/10 - 0s - 9ms/step - loss: 3.6951e-09
Epoch 931/5000
10/10 - 0s - 9ms/step - loss: 1.0127e-09
Epoch 932/5000
10/10 - 0s - 9ms/step - loss: 2.4220e-09
Epoch 933/5000
10/10 - 0s - 9ms/step - loss: 4.7213e-10
Epoch 934/5000
10/10 - 0s - 8ms/step - loss: 3.7982e-10
Epoch 935/5000
10/10 - 0s - 7ms/step - loss: 3.4065e-09
Epoch 936/5000
10/10 - 0s - 8ms/step - loss: 7.7860e-08
Epoch 937/5000
10/10 - 0s - 10ms/step - loss: 3.1531e-07
Epoch 938/5000
10/10 - 0s - 7ms/step - loss: 7.8724e-08
Epoch 939/5000
10/10 - 0s - 8ms/step - loss: 2.6482e-08
Epoch 940/5000
10/10 - 0s - 9ms/step - loss: 7.3177e-09
Epoch 941/5000
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Epoch 942/5000
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Epoch 943/5000
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Epoch 944/5000
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Epoch 945/5000
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Epoch 946/5000
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Epoch 947/5000
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Epoch 948/5000
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Epoch 949/5000
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Epoch 950/5000
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Epoch 951/5000
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Epoch 952/5000
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Epoch 953/5000
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Epoch 954/5000
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Epoch 955/5000
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Epoch 956/5000
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Epoch 957/5000
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Epoch 958/5000
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Epoch 959/5000
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Epoch 960/5000
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Epoch 961/5000
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Epoch 962/5000
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Epoch 963/5000
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Epoch 964/5000
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Epoch 965/5000
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Epoch 966/5000
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Epoch 967/5000
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Epoch 968/5000
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Epoch 969/5000
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Epoch 970/5000
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Epoch 971/5000
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Epoch 972/5000
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Epoch 973/5000
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Epoch 974/5000
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Epoch 975/5000
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Epoch 976/5000
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Epoch 977/5000
10/10 - 0s - 8ms/step - loss: 1.2520e-08
Epoch 978/5000
10/10 - 0s - 9ms/step - loss: 6.3029e-09
Epoch 979/5000
10/10 - 0s - 8ms/step - loss: 2.0675e-10
Epoch 980/5000
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Epoch 981/5000
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Epoch 982/5000
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Epoch 983/5000
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Epoch 984/5000
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Epoch 985/5000
10/10 - 0s - 9ms/step - loss: 3.7127e-07
Epoch 986/5000
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Epoch 987/5000
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Epoch 988/5000
10/10 - 0s - 10ms/step - loss: 8.9082e-09
Epoch 989/5000
10/10 - 0s - 10ms/step - loss: 4.9268e-09
Epoch 990/5000
10/10 - 0s - 20ms/step - loss: 1.6713e-09
Epoch 991/5000
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Epoch 992/5000
10/10 - 0s - 13ms/step - loss: 3.9300e-10
Epoch 993/5000
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Epoch 994/5000
10/10 - 0s - 11ms/step - loss: 4.0350e-10
Epoch 995/5000
10/10 - 0s - 9ms/step - loss: 5.3824e-11
Epoch 996/5000
10/10 - 0s - 8ms/step - loss: 5.0931e-11
Epoch 997/5000
10/10 - 0s - 8ms/step - loss: 7.3427e-10
Epoch 998/5000
10/10 - 0s - 8ms/step - loss: 1.8558e-08
Epoch 999/5000
10/10 - 0s - 8ms/step - loss: 2.1726e-07
Epoch 1000/5000
10/10 - 0s - 10ms/step - loss: 2.3873e-07
Epoch 1001/5000
10/10 - 0s - 7ms/step - loss: 6.5046e-08
Epoch 1002/5000
10/10 - 0s - 9ms/step - loss: 1.9212e-08
Epoch 1003/5000
10/10 - 0s - 8ms/step - loss: 4.6049e-09
Epoch 1004/5000
10/10 - 0s - 8ms/step - loss: 2.5097e-09
Epoch 1005/5000
10/10 - 0s - 8ms/step - loss: 1.2752e-09
Epoch 1006/5000
10/10 - 0s - 8ms/step - loss: 8.3775e-10
Epoch 1007/5000
10/10 - 0s - 8ms/step - loss: 4.0171e-09
Epoch 1008/5000
10/10 - 0s - 9ms/step - loss: 7.1285e-09
Epoch 1009/5000
10/10 - 0s - 8ms/step - loss: 2.1765e-08
Epoch 1010/5000
10/10 - 0s - 9ms/step - loss: 1.4909e-07
Epoch 1011/5000
10/10 - 0s - 8ms/step - loss: 1.7535e-07
Epoch 1012/5000
10/10 - 0s - 8ms/step - loss: 6.7427e-08
Epoch 1013/5000
10/10 - 0s - 9ms/step - loss: 2.2823e-08
Epoch 1014/5000
10/10 - 0s - 8ms/step - loss: 9.3872e-09
Epoch 1015/5000
10/10 - 0s - 8ms/step - loss: 9.6921e-09
Epoch 1016/5000
10/10 - 0s - 10ms/step - loss: 8.7247e-09
Epoch 1017/5000
10/10 - 0s - 9ms/step - loss: 2.8769e-09
Epoch 1018/5000
10/10 - 0s - 8ms/step - loss: 3.5970e-10
Epoch 1019/5000
10/10 - 0s - 9ms/step - loss: 6.1831e-09
Epoch 1020/5000
10/10 - 0s - 9ms/step - loss: 7.9055e-08
Epoch 1021/5000
10/10 - 0s - 7ms/step - loss: 4.5606e-07
Epoch 1022/5000
10/10 - 0s - 9ms/step - loss: 1.0381e-07
Epoch 1023/5000
10/10 - 0s - 8ms/step - loss: 4.1241e-08
Epoch 1024/5000
10/10 - 0s - 8ms/step - loss: 1.6370e-08
Epoch 1025/5000
10/10 - 0s - 9ms/step - loss: 7.5151e-09
Epoch 1026/5000
10/10 - 0s - 10ms/step - loss: 2.4982e-09
Epoch 1027/5000
10/10 - 0s - 8ms/step - loss: 1.1561e-09
Epoch 1028/5000
10/10 - 0s - 8ms/step - loss: 7.3225e-10
Epoch 1029/5000
10/10 - 0s - 10ms/step - loss: 7.1077e-10
Epoch 1030/5000
10/10 - 0s - 8ms/step - loss: 1.3337e-09
Epoch 1031/5000
10/10 - 0s - 9ms/step - loss: 4.1710e-09
Epoch 1032/5000
10/10 - 0s - 8ms/step - loss: 5.1892e-09
Epoch 1033/5000
10/10 - 0s - 8ms/step - loss: 5.5316e-08
Epoch 1034/5000
10/10 - 0s - 8ms/step - loss: 2.8163e-07
Epoch 1035/5000
10/10 - 0s - 9ms/step - loss: 6.1763e-08
Epoch 1036/5000
10/10 - 0s - 9ms/step - loss: 2.9809e-08
Epoch 1037/5000
10/10 - 0s - 9ms/step - loss: 1.5970e-08
Epoch 1038/5000
10/10 - 0s - 8ms/step - loss: 9.7905e-09
Epoch 1039/5000
10/10 - 0s - 8ms/step - loss: 1.0506e-09
Epoch 1040/5000
10/10 - 0s - 8ms/step - loss: 2.5367e-09
Epoch 1041/5000
10/10 - 0s - 8ms/step - loss: 1.4800e-08
Epoch 1042/5000
10/10 - 0s - 7ms/step - loss: 5.8778e-08
Epoch 1043/5000
10/10 - 0s - 8ms/step - loss: 2.0709e-07
Epoch 1044/5000
10/10 - 0s - 8ms/step - loss: 5.3306e-08
Epoch 1045/5000
10/10 - 0s - 9ms/step - loss: 3.2224e-08
Epoch 1046/5000
10/10 - 0s - 8ms/step - loss: 8.5754e-09
Epoch 1047/5000
10/10 - 0s - 7ms/step - loss: 4.6333e-09
Epoch 1048/5000
10/10 - 0s - 9ms/step - loss: 6.1914e-09
Epoch 1049/5000
10/10 - 0s - 8ms/step - loss: 4.1494e-08
Epoch 1050/5000
10/10 - 0s - 21ms/step - loss: 1.4574e-07
Epoch 1051/5000
10/10 - 0s - 9ms/step - loss: 6.4252e-08
Epoch 1052/5000
10/10 - 0s - 9ms/step - loss: 2.4115e-08
Epoch 1053/5000
10/10 - 0s - 8ms/step - loss: 1.2558e-08
Epoch 1054/5000
10/10 - 0s - 9ms/step - loss: 2.4022e-09
Epoch 1055/5000
10/10 - 0s - 8ms/step - loss: 2.8953e-08
Epoch 1056/5000
10/10 - 0s - 8ms/step - loss: 1.5389e-07
Epoch 1057/5000
10/10 - 0s - 9ms/step - loss: 1.4533e-07
Epoch 1058/5000
10/10 - 0s - 8ms/step - loss: 4.5541e-08
Epoch 1059/5000
10/10 - 0s - 14ms/step - loss: 8.4660e-09
Epoch 1060/5000
10/10 - 0s - 12ms/step - loss: 6.3524e-09
Epoch 1061/5000
10/10 - 0s - 8ms/step - loss: 2.8551e-09
Epoch 1062/5000
10/10 - 0s - 8ms/step - loss: 1.7066e-08
Epoch 1063/5000
10/10 - 0s - 10ms/step - loss: 3.6229e-08
Epoch 1064/5000
10/10 - 0s - 8ms/step - loss: 1.0466e-07
Epoch 1065/5000
10/10 - 0s - 9ms/step - loss: 1.6822e-07
Epoch 1066/5000
10/10 - 0s - 9ms/step - loss: 1.9174e-08
Epoch 1067/5000
10/10 - 0s - 8ms/step - loss: 1.5147e-08
Epoch 1068/5000
10/10 - 0s - 9ms/step - loss: 5.3570e-09
Epoch 1069/5000
10/10 - 0s - 8ms/step - loss: 5.2863e-09
Epoch 1070/5000
10/10 - 0s - 9ms/step - loss: 8.2176e-09
Epoch 1071/5000
10/10 - 0s - 8ms/step - loss: 1.2889e-07
Epoch 1072/5000
10/10 - 0s - 8ms/step - loss: 2.8298e-07
Epoch 1073/5000
10/10 - 0s - 9ms/step - loss: 7.1446e-08
Epoch 1074/5000
10/10 - 0s - 9ms/step - loss: 2.5284e-08
Epoch 1075/5000
10/10 - 0s - 9ms/step - loss: 1.3791e-08
Epoch 1076/5000
10/10 - 0s - 8ms/step - loss: 5.1916e-09
Epoch 1077/5000
10/10 - 0s - 9ms/step - loss: 3.0023e-09
Epoch 1078/5000
10/10 - 0s - 9ms/step - loss: 4.6184e-09
Epoch 1079/5000
10/10 - 0s - 9ms/step - loss: 3.2151e-10
Epoch 1080/5000
10/10 - 0s - 9ms/step - loss: 4.6665e-12
Epoch 1081/5000
10/10 - 0s - 7ms/step - loss: 1.6188e-09
Epoch 1082/5000
10/10 - 0s - 9ms/step - loss: 9.7461e-08
Epoch 1083/5000
10/10 - 0s - 9ms/step - loss: 4.4299e-07
Epoch 1084/5000
10/10 - 0s - 8ms/step - loss: 1.0744e-07
Epoch 1085/5000
10/10 - 0s - 8ms/step - loss: 5.0966e-08
Epoch 1086/5000
10/10 - 0s - 9ms/step - loss: 1.9620e-08
Epoch 1087/5000
10/10 - 0s - 8ms/step - loss: 5.9925e-09
Epoch 1088/5000
10/10 - 0s - 8ms/step - loss: 2.2455e-09
Epoch 1089/5000
10/10 - 0s - 9ms/step - loss: 1.0223e-09
Epoch 1090/5000
10/10 - 0s - 8ms/step - loss: 1.1510e-09
Epoch 1091/5000
10/10 - 0s - 9ms/step - loss: 1.9312e-10
Epoch 1092/5000
10/10 - 0s - 9ms/step - loss: 1.2609e-09
Epoch 1093/5000
10/10 - 0s - 9ms/step - loss: 4.3924e-10
Epoch 1094/5000
10/10 - 0s - 7ms/step - loss: 5.1341e-09
Epoch 1095/5000
10/10 - 0s - 7ms/step - loss: 2.2870e-08
Epoch 1096/5000
10/10 - 0s - 9ms/step - loss: 2.5991e-07
Epoch 1097/5000
10/10 - 0s - 9ms/step - loss: 1.7106e-07
Epoch 1098/5000
10/10 - 0s - 9ms/step - loss: 6.4031e-08
Epoch 1099/5000
10/10 - 0s - 9ms/step - loss: 2.4757e-08
Epoch 1100/5000
10/10 - 0s - 9ms/step - loss: 8.7437e-09
Epoch 1101/5000
10/10 - 0s - 9ms/step - loss: 2.7090e-09
Epoch 1102/5000
10/10 - 0s - 10ms/step - loss: 2.4872e-09
Epoch 1103/5000
10/10 - 0s - 8ms/step - loss: 4.5978e-10
Epoch 1104/5000
10/10 - 0s - 9ms/step - loss: 3.8141e-10
Epoch 1105/5000
10/10 - 0s - 18ms/step - loss: 4.5367e-11
Epoch 1106/5000
10/10 - 0s - 18ms/step - loss: 6.9774e-09
Epoch 1107/5000
10/10 - 0s - 16ms/step - loss: 1.6984e-07
Epoch 1108/5000
10/10 - 0s - 8ms/step - loss: 3.5449e-07
Epoch 1109/5000
10/10 - 0s - 9ms/step - loss: 9.6216e-08
Epoch 1110/5000
10/10 - 0s - 8ms/step - loss: 3.5450e-08
Epoch 1111/5000
10/10 - 0s - 9ms/step - loss: 1.1538e-08
Epoch 1112/5000
10/10 - 0s - 9ms/step - loss: 4.8163e-09
Epoch 1113/5000
10/10 - 0s - 8ms/step - loss: 1.0733e-09
Epoch 1114/5000
10/10 - 0s - 9ms/step - loss: 3.7546e-10
Epoch 1115/5000
10/10 - 0s - 9ms/step - loss: 1.3159e-10
Epoch 1116/5000
10/10 - 0s - 8ms/step - loss: 3.6567e-10
Epoch 1117/5000
10/10 - 0s - 9ms/step - loss: 3.8590e-10
Epoch 1118/5000
10/10 - 0s - 8ms/step - loss: 1.1043e-10
Epoch 1119/5000
10/10 - 0s - 7ms/step - loss: 1.3050e-09
Epoch 1120/5000
10/10 - 0s - 8ms/step - loss: 5.7067e-08
Epoch 1121/5000
10/10 - 0s - 8ms/step - loss: 5.2858e-07
Epoch 1122/5000
10/10 - 0s - 12ms/step - loss: 1.1662e-07
Epoch 1123/5000
10/10 - 0s - 14ms/step - loss: 4.8577e-08
Epoch 1124/5000
10/10 - 0s - 9ms/step - loss: 1.8565e-08
Epoch 1125/5000
10/10 - 0s - 9ms/step - loss: 3.9257e-09
Epoch 1126/5000
10/10 - 0s - 9ms/step - loss: 7.2744e-10
Epoch 1127/5000
10/10 - 0s - 10ms/step - loss: 1.2672e-10
Epoch 1128/5000
10/10 - 0s - 9ms/step - loss: 3.2562e-10
Epoch 1129/5000
10/10 - 0s - 8ms/step - loss: 3.3545e-10
Epoch 1130/5000
10/10 - 0s - 10ms/step - loss: 1.5995e-09
Epoch 1131/5000
10/10 - 0s - 8ms/step - loss: 2.9176e-09
Epoch 1132/5000
10/10 - 0s - 8ms/step - loss: 8.3673e-10
Epoch 1133/5000
10/10 - 0s - 9ms/step - loss: 3.1002e-09
Epoch 1134/5000
10/10 - 0s - 9ms/step - loss: 4.8940e-08
Epoch 1135/5000
10/10 - 0s - 9ms/step - loss: 3.1131e-07
Epoch 1136/5000
10/10 - 0s - 9ms/step - loss: 9.0422e-08
Epoch 1137/5000
10/10 - 0s - 10ms/step - loss: 3.6459e-08
Epoch 1138/5000
10/10 - 0s - 8ms/step - loss: 1.8408e-08
Epoch 1139/5000
10/10 - 0s - 9ms/step - loss: 6.5788e-09
Epoch 1140/5000
10/10 - 0s - 7ms/step - loss: 2.5175e-09
Epoch 1141/5000
10/10 - 0s - 8ms/step - loss: 2.8567e-09
Epoch 1142/5000
10/10 - 0s - 7ms/step - loss: 7.7980e-10
Epoch 1143/5000
10/10 - 0s - 8ms/step - loss: 8.1691e-09
Epoch 1144/5000
10/10 - 0s - 8ms/step - loss: 9.8564e-08
Epoch 1145/5000
10/10 - 0s - 11ms/step - loss: 2.5834e-07
Epoch 1146/5000
10/10 - 0s - 13ms/step - loss: 6.5753e-08
Epoch 1147/5000
10/10 - 0s - 9ms/step - loss: 1.9869e-08
Epoch 1148/5000
10/10 - 0s - 8ms/step - loss: 6.7011e-09
Epoch 1149/5000
10/10 - 0s - 9ms/step - loss: 5.2367e-09
Epoch 1150/5000
10/10 - 0s - 9ms/step - loss: 9.3110e-11
Epoch 1151/5000
10/10 - 0s - 9ms/step - loss: 1.1470e-12
Epoch 1152/5000
10/10 - 0s - 9ms/step - loss: 2.5135e-10
Epoch 1153/5000
10/10 - 0s - 9ms/step - loss: 6.5576e-09
Epoch 1154/5000
10/10 - 0s - 9ms/step - loss: 1.0988e-07
Epoch 1155/5000
10/10 - 0s - 7ms/step - loss: 4.2752e-07
Epoch 1156/5000
10/10 - 0s - 9ms/step - loss: 1.0634e-07
Epoch 1157/5000
10/10 - 0s - 8ms/step - loss: 4.8469e-08
Epoch 1158/5000
10/10 - 0s - 9ms/step - loss: 1.8636e-08
Epoch 1159/5000
10/10 - 0s - 8ms/step - loss: 7.3934e-09
Epoch 1160/5000
10/10 - 0s - 9ms/step - loss: 3.0284e-09
Epoch 1161/5000
10/10 - 0s - 8ms/step - loss: 1.2891e-09
Epoch 1162/5000
10/10 - 0s - 9ms/step - loss: 3.9508e-10
Epoch 1163/5000
10/10 - 0s - 8ms/step - loss: 3.6484e-10
Epoch 1164/5000
10/10 - 0s - 9ms/step - loss: 2.1562e-10
Epoch 1165/5000
10/10 - 0s - 9ms/step - loss: 3.5278e-09
Epoch 1166/5000
10/10 - 0s - 8ms/step - loss: 2.1866e-09
Epoch 1167/5000
10/10 - 0s - 9ms/step - loss: 1.8568e-09
Epoch 1168/5000
10/10 - 0s - 8ms/step - loss: 6.5217e-10
Epoch 1169/5000
10/10 - 0s - 9ms/step - loss: 4.8410e-10
Epoch 1170/5000
10/10 - 0s - 8ms/step - loss: 9.0175e-08
Epoch 1171/5000
10/10 - 0s - 10ms/step - loss: 9.0385e-07
Epoch 1172/5000
10/10 - 0s - 8ms/step - loss: 3.2407e-07
Epoch 1173/5000
10/10 - 0s - 7ms/step - loss: 9.8181e-08
Epoch 1174/5000
10/10 - 0s - 9ms/step - loss: 3.0998e-08
Epoch 1175/5000
10/10 - 0s - 9ms/step - loss: 1.0883e-08
Epoch 1176/5000
10/10 - 0s - 9ms/step - loss: 3.8010e-09
Epoch 1177/5000
10/10 - 0s - 9ms/step - loss: 1.5250e-09
Epoch 1178/5000
10/10 - 0s - 9ms/step - loss: 7.3995e-10
Epoch 1179/5000
10/10 - 0s - 9ms/step - loss: 1.9590e-10
Epoch 1180/5000
10/10 - 0s - 8ms/step - loss: 8.8649e-11
Epoch 1181/5000
10/10 - 0s - 8ms/step - loss: 1.0963e-10
Epoch 1182/5000
10/10 - 0s - 9ms/step - loss: 3.3264e-11
Epoch 1183/5000
10/10 - 0s - 10ms/step - loss: 7.3676e-11
Epoch 1184/5000
10/10 - 0s - 14ms/step - loss: 1.2510e-10
Epoch 1185/5000
10/10 - 0s - 13ms/step - loss: 4.8234e-11
Epoch 1186/5000
10/10 - 0s - 9ms/step - loss: 3.0763e-10
Epoch 1187/5000
10/10 - 0s - 8ms/step - loss: 2.2587e-10
Epoch 1188/5000
10/10 - 0s - 8ms/step - loss: 2.2081e-10
Epoch 1189/5000
10/10 - 0s - 11ms/step - loss: 1.8252e-10
Epoch 1190/5000
10/10 - 0s - 17ms/step - loss: 6.3822e-10
Epoch 1191/5000
10/10 - 0s - 8ms/step - loss: 2.6525e-10
Epoch 1192/5000
10/10 - 0s - 9ms/step - loss: 3.5212e-09
Epoch 1193/5000
10/10 - 0s - 8ms/step - loss: 9.0556e-09
Epoch 1194/5000
10/10 - 0s - 8ms/step - loss: 4.0416e-08
Epoch 1195/5000
10/10 - 0s - 9ms/step - loss: 2.4533e-07
Epoch 1196/5000
10/10 - 0s - 7ms/step - loss: 1.1296e-07
Epoch 1197/5000
10/10 - 0s - 9ms/step - loss: 4.1737e-08
Epoch 1198/5000
10/10 - 0s - 10ms/step - loss: 1.6163e-08
Epoch 1199/5000
10/10 - 0s - 8ms/step - loss: 4.2463e-09
Epoch 1200/5000
10/10 - 0s - 9ms/step - loss: 3.6259e-09
Epoch 1201/5000
10/10 - 0s - 9ms/step - loss: 2.0974e-09
Epoch 1202/5000
10/10 - 0s - 9ms/step - loss: 1.5285e-08
Epoch 1203/5000
10/10 - 0s - 8ms/step - loss: 9.0733e-08
Epoch 1204/5000
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Epoch 1205/5000
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Epoch 1206/5000
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Epoch 1207/5000
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Epoch 1208/5000
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Epoch 1209/5000
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Epoch 1210/5000
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Epoch 1211/5000
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Epoch 1212/5000
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Epoch 1213/5000
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Epoch 1214/5000
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Epoch 1215/5000
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Epoch 1216/5000
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Epoch 1217/5000
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Epoch 1218/5000
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Epoch 1219/5000
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Epoch 1220/5000
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Epoch 1221/5000
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Epoch 1222/5000
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Epoch 1223/5000
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Epoch 1224/5000
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Epoch 1225/5000
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Epoch 1226/5000
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Epoch 1227/5000
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Epoch 1228/5000
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Epoch 1229/5000
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Epoch 1230/5000
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Epoch 1231/5000
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Epoch 1232/5000
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Epoch 1233/5000
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Epoch 1234/5000
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Epoch 1235/5000
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Epoch 1236/5000
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Epoch 1237/5000
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Epoch 1238/5000
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Epoch 1239/5000
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Epoch 1240/5000
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Epoch 1241/5000
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Epoch 1242/5000
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Epoch 1243/5000
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Epoch 1244/5000
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Epoch 1245/5000
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Epoch 1246/5000
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Epoch 1247/5000
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Epoch 1248/5000
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Epoch 1249/5000
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Epoch 1250/5000
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Epoch 1251/5000
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Epoch 1252/5000
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Epoch 1253/5000
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Epoch 1254/5000
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Epoch 1255/5000
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Epoch 1256/5000
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Epoch 1257/5000
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Epoch 1258/5000
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Epoch 1259/5000
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Epoch 1260/5000
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Epoch 1261/5000
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Epoch 1262/5000
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Epoch 1263/5000
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Epoch 1264/5000
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Epoch 1265/5000
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Epoch 1266/5000
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Epoch 1267/5000
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Epoch 1268/5000
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Epoch 1269/5000
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Epoch 1270/5000
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Epoch 1271/5000
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Epoch 1272/5000
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Epoch 1273/5000
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Epoch 1274/5000
10/10 - 0s - 9ms/step - loss: 7.0766e-08
Epoch 1275/5000
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Epoch 1276/5000
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Epoch 1277/5000
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Epoch 1278/5000
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Epoch 1279/5000
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Epoch 1280/5000
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Epoch 1281/5000
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Epoch 1282/5000
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Epoch 1283/5000
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Epoch 1284/5000
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Epoch 1285/5000
10/10 - 0s - 11ms/step - loss: 3.3019e-08
Epoch 1286/5000
10/10 - 0s - 9ms/step - loss: 8.9346e-09
Epoch 1287/5000
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Epoch 1288/5000
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Epoch 1289/5000
10/10 - 0s - 8ms/step - loss: 3.7560e-10
Epoch 1290/5000
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Epoch 1291/5000
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Epoch 1292/5000
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Epoch 1293/5000
10/10 - 0s - 9ms/step - loss: 8.6533e-08
Epoch 1294/5000
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Epoch 1295/5000
10/10 - 0s - 10ms/step - loss: 9.7911e-09
Epoch 1296/5000
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Epoch 1297/5000
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Epoch 1298/5000
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Epoch 1299/5000
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Epoch 1300/5000
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Epoch 1301/5000
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Epoch 1302/5000
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Epoch 1303/5000
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Epoch 1304/5000
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Epoch 1305/5000
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Epoch 1306/5000
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Epoch 1307/5000
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Epoch 1308/5000
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Epoch 1309/5000
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Epoch 1310/5000
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Epoch 1311/5000
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Epoch 1312/5000
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Epoch 1313/5000
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Epoch 1314/5000
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Epoch 1315/5000
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Epoch 1316/5000
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Epoch 1317/5000
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Epoch 1318/5000
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Epoch 1319/5000
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Epoch 1320/5000
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Epoch 1321/5000
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Epoch 1322/5000
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Epoch 1323/5000
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Epoch 1324/5000
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Epoch 1325/5000
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Epoch 1326/5000
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Epoch 1327/5000
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Epoch 1328/5000
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Epoch 1329/5000
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Epoch 1330/5000
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Epoch 1331/5000
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Epoch 1332/5000
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Epoch 1333/5000
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Epoch 1334/5000
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Epoch 1335/5000
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Epoch 1336/5000
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Epoch 1337/5000
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Epoch 1338/5000
10/10 - 0s - 10ms/step - loss: 3.0745e-09
Epoch 1339/5000
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Epoch 1340/5000
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Epoch 1341/5000
10/10 - 0s - 8ms/step - loss: 1.6203e-07
Epoch 1342/5000
10/10 - 0s - 9ms/step - loss: 4.1088e-08
Epoch 1343/5000
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Epoch 1344/5000
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Epoch 1345/5000
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Epoch 1346/5000
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Epoch 1347/5000
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Epoch 1348/5000
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Epoch 1349/5000
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Epoch 1350/5000
10/10 - 0s - 9ms/step - loss: 6.4381e-08
Epoch 1351/5000
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Epoch 1352/5000
10/10 - 0s - 10ms/step - loss: 6.9470e-09
Epoch 1353/5000
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Epoch 1354/5000
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Epoch 1355/5000
10/10 - 0s - 8ms/step - loss: 9.4905e-10
Epoch 1356/5000
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Epoch 1357/5000
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Epoch 1358/5000
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Epoch 1359/5000
10/10 - 0s - 7ms/step - loss: 3.3828e-07
Epoch 1360/5000
10/10 - 0s - 10ms/step - loss: 7.7446e-08
Epoch 1361/5000
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Epoch 1362/5000
10/10 - 0s - 9ms/step - loss: 8.7067e-09
Epoch 1363/5000
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Epoch 1364/5000
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Epoch 1365/5000
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Epoch 1366/5000
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Epoch 1367/5000
10/10 - 0s - 10ms/step - loss: 8.3029e-10
Epoch 1368/5000
10/10 - 0s - 9ms/step - loss: 1.0333e-09
Epoch 1369/5000
10/10 - 0s - 9ms/step - loss: 8.1532e-09
Epoch 1370/5000
10/10 - 0s - 9ms/step - loss: 2.6290e-07
Epoch 1371/5000
10/10 - 0s - 10ms/step - loss: 3.9124e-07
Epoch 1372/5000
10/10 - 0s - 8ms/step - loss: 1.1581e-07
Epoch 1373/5000
10/10 - 0s - 10ms/step - loss: 2.9691e-08
Epoch 1374/5000
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Epoch 1375/5000
10/10 - 0s - 10ms/step - loss: 5.1802e-09
Epoch 1376/5000
10/10 - 0s - 9ms/step - loss: 2.6146e-09
Epoch 1377/5000
10/10 - 0s - 9ms/step - loss: 1.1974e-09
Epoch 1378/5000
10/10 - 0s - 9ms/step - loss: 1.7989e-09
Epoch 1379/5000
10/10 - 0s - 18ms/step - loss: 9.4086e-10
Epoch 1380/5000
10/10 - 0s - 9ms/step - loss: 1.3682e-10
Epoch 1381/5000
10/10 - 0s - 10ms/step - loss: 1.2405e-10
Epoch 1382/5000
10/10 - 0s - 9ms/step - loss: 5.2723e-10
Epoch 1383/5000
10/10 - 0s - 8ms/step - loss: 1.7385e-09
Epoch 1384/5000
10/10 - 0s - 10ms/step - loss: 6.6951e-09
Epoch 1385/5000
10/10 - 0s - 9ms/step - loss: 6.1050e-08
Epoch 1386/5000
10/10 - 0s - 9ms/step - loss: 3.2618e-07
Epoch 1387/5000
10/10 - 0s - 10ms/step - loss: 7.3047e-08
Epoch 1388/5000
10/10 - 0s - 8ms/step - loss: 3.1499e-08
Epoch 1389/5000
10/10 - 0s - 10ms/step - loss: 1.4786e-08
Epoch 1390/5000
10/10 - 0s - 8ms/step - loss: 7.9683e-09
Epoch 1391/5000
10/10 - 0s - 8ms/step - loss: 9.5775e-09
Epoch 1392/5000
10/10 - 0s - 10ms/step - loss: 2.6719e-09
Epoch 1393/5000
10/10 - 0s - 9ms/step - loss: 4.0366e-09
Epoch 1394/5000
10/10 - 0s - 9ms/step - loss: 2.9098e-10
Epoch 1395/5000
10/10 - 0s - 9ms/step - loss: 2.5211e-09
Epoch 1396/5000
10/10 - 0s - 9ms/step - loss: 3.9066e-08
Epoch 1397/5000
10/10 - 0s - 9ms/step - loss: 4.5935e-07
Epoch 1398/5000
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Epoch 1399/5000
10/10 - 0s - 8ms/step - loss: 3.9916e-08
Epoch 1400/5000
10/10 - 0s - 9ms/step - loss: 1.6826e-08
Epoch 1401/5000
10/10 - 0s - 8ms/step - loss: 6.5645e-09
Epoch 1402/5000
10/10 - 0s - 9ms/step - loss: 1.3912e-09
Epoch 1403/5000
10/10 - 0s - 8ms/step - loss: 4.5217e-10
Epoch 1404/5000
10/10 - 0s - 10ms/step - loss: 1.0211e-10
Epoch 1405/5000
10/10 - 0s - 8ms/step - loss: 8.1722e-11
Epoch 1406/5000
10/10 - 0s - 10ms/step - loss: 5.7305e-10
Epoch 1407/5000
10/10 - 0s - 10ms/step - loss: 1.2803e-10
Epoch 1408/5000
10/10 - 0s - 8ms/step - loss: 1.2262e-11
Epoch 1409/5000
10/10 - 0s - 8ms/step - loss: 2.0693e-09
Epoch 1410/5000
10/10 - 0s - 9ms/step - loss: 5.7685e-08
Epoch 1411/5000
10/10 - 0s - 8ms/step - loss: 5.2550e-07
Epoch 1412/5000
10/10 - 0s - 8ms/step - loss: 1.2357e-07
Epoch 1413/5000
10/10 - 0s - 10ms/step - loss: 5.3704e-08
Epoch 1414/5000
10/10 - 0s - 9ms/step - loss: 1.9713e-08
Epoch 1415/5000
10/10 - 0s - 9ms/step - loss: 4.2274e-09
Epoch 1416/5000
10/10 - 0s - 8ms/step - loss: 1.8531e-09
Epoch 1417/5000
10/10 - 0s - 8ms/step - loss: 3.8277e-10
Epoch 1418/5000
10/10 - 0s - 9ms/step - loss: 5.2057e-10
Epoch 1419/5000
10/10 - 0s - 10ms/step - loss: 3.5893e-11
Epoch 1420/5000
10/10 - 0s - 10ms/step - loss: 8.8646e-10
Epoch 1421/5000
10/10 - 0s - 8ms/step - loss: 2.0432e-10
Epoch 1422/5000
10/10 - 0s - 8ms/step - loss: 5.2795e-10
Epoch 1423/5000
10/10 - 0s - 22ms/step - loss: 4.1709e-09
Epoch 1424/5000
10/10 - 0s - 8ms/step - loss: 3.8746e-08
Epoch 1425/5000
10/10 - 0s - 10ms/step - loss: 2.0663e-07
Epoch 1426/5000
10/10 - 0s - 9ms/step - loss: 7.8229e-08
Epoch 1427/5000
10/10 - 0s - 9ms/step - loss: 4.5192e-08
Epoch 1428/5000
10/10 - 0s - 9ms/step - loss: 1.2491e-08
Epoch 1429/5000
10/10 - 0s - 9ms/step - loss: 4.3501e-09
Epoch 1430/5000
10/10 - 0s - 9ms/step - loss: 6.4295e-09
Epoch 1431/5000
10/10 - 0s - 9ms/step - loss: 4.8164e-09
Epoch 1432/5000
10/10 - 0s - 14ms/step - loss: 8.3180e-09
Epoch 1433/5000
10/10 - 0s - 18ms/step - loss: 6.8439e-08
Epoch 1434/5000
10/10 - 0s - 18ms/step - loss: 3.8901e-07
Epoch 1435/5000
10/10 - 0s - 13ms/step - loss: 8.9918e-08
Epoch 1436/5000
10/10 - 0s - 8ms/step - loss: 3.6423e-08
Epoch 1437/5000
10/10 - 0s - 9ms/step - loss: 1.3274e-08
Epoch 1438/5000
10/10 - 0s - 10ms/step - loss: 5.9495e-09
Epoch 1439/5000
10/10 - 0s - 9ms/step - loss: 3.3608e-09
Epoch 1440/5000
10/10 - 0s - 10ms/step - loss: 2.1482e-09
Epoch 1441/5000
10/10 - 0s - 9ms/step - loss: 3.8693e-09
Epoch 1442/5000
10/10 - 0s - 9ms/step - loss: 2.3747e-09
Epoch 1443/5000
10/10 - 0s - 9ms/step - loss: 5.2669e-09
Epoch 1444/5000
10/10 - 0s - 9ms/step - loss: 3.9976e-09
Epoch 1445/5000
10/10 - 0s - 10ms/step - loss: 4.6945e-08
Epoch 1446/5000
10/10 - 0s - 9ms/step - loss: 3.2520e-07
Epoch 1447/5000
10/10 - 0s - 8ms/step - loss: 8.0044e-08
Epoch 1448/5000
10/10 - 0s - 8ms/step - loss: 3.0318e-08
Epoch 1449/5000
10/10 - 0s - 9ms/step - loss: 1.0337e-08
Epoch 1450/5000
10/10 - 0s - 9ms/step - loss: 5.1845e-09
Epoch 1451/5000
10/10 - 0s - 7ms/step - loss: 9.5958e-10
Epoch 1452/5000
10/10 - 0s - 8ms/step - loss: 2.7132e-09
Epoch 1453/5000
10/10 - 0s - 8ms/step - loss: 5.3379e-09
Epoch 1454/5000
10/10 - 0s - 10ms/step - loss: 6.4202e-10
Epoch 1455/5000
10/10 - 0s - 9ms/step - loss: 1.6222e-08
Epoch 1456/5000
10/10 - 0s - 8ms/step - loss: 1.9563e-07
Epoch 1457/5000
10/10 - 0s - 9ms/step - loss: 2.0990e-07
Epoch 1458/5000
10/10 - 0s - 8ms/step - loss: 6.1130e-08
Epoch 1459/5000
10/10 - 0s - 8ms/step - loss: 1.9231e-08
Epoch 1460/5000
10/10 - 0s - 10ms/step - loss: 8.5499e-09
Epoch 1461/5000
10/10 - 0s - 8ms/step - loss: 2.0923e-09
Epoch 1462/5000
10/10 - 0s - 21ms/step - loss: 8.1763e-10
Epoch 1463/5000
10/10 - 0s - 9ms/step - loss: 8.9028e-10
Epoch 1464/5000
10/10 - 0s - 17ms/step - loss: 4.0735e-09
Epoch 1465/5000
10/10 - 0s - 9ms/step - loss: 4.5490e-08
Epoch 1466/5000
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Epoch 1467/5000
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Epoch 1468/5000
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Epoch 1469/5000
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Epoch 1470/5000
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Epoch 1471/5000
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Epoch 1472/5000
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Epoch 1473/5000
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Epoch 1474/5000
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Epoch 1475/5000
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Epoch 1476/5000
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Epoch 1477/5000
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Epoch 1478/5000
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Epoch 1479/5000
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Epoch 1480/5000
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Epoch 1481/5000
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Epoch 1482/5000
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Epoch 1483/5000
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Epoch 1484/5000
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Epoch 1485/5000
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Epoch 1486/5000
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Epoch 1487/5000
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Epoch 1488/5000
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Epoch 1489/5000
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Epoch 1490/5000
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Epoch 1491/5000
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Epoch 1492/5000
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Epoch 1493/5000
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Epoch 1494/5000
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Epoch 1495/5000
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Epoch 1496/5000
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Epoch 1497/5000
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Epoch 1498/5000
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Epoch 1499/5000
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Epoch 1500/5000
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Epoch 1501/5000
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Epoch 1502/5000
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Epoch 1503/5000
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Epoch 1504/5000
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Epoch 1505/5000
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Epoch 1506/5000
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Epoch 1507/5000
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Epoch 1508/5000
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Epoch 1509/5000
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Epoch 1510/5000
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Epoch 1511/5000
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Epoch 1512/5000
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Epoch 1513/5000
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Epoch 1514/5000
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Epoch 1515/5000
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Epoch 1516/5000
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Epoch 1517/5000
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Epoch 1518/5000
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Epoch 1519/5000
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Epoch 1520/5000
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Epoch 1521/5000
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Epoch 1522/5000
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Epoch 1523/5000
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Epoch 1524/5000
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Epoch 1525/5000
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Epoch 1526/5000
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Epoch 1527/5000
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Epoch 1528/5000
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Epoch 1529/5000
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Epoch 1530/5000
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Epoch 1531/5000
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Epoch 1532/5000
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Epoch 1533/5000
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Epoch 1534/5000
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Epoch 1535/5000
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Epoch 1536/5000
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Epoch 1537/5000
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Epoch 1538/5000
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Epoch 1539/5000
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Epoch 1540/5000
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Epoch 1541/5000
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Epoch 1542/5000
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Epoch 1543/5000
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Epoch 1544/5000
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Epoch 1545/5000
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Epoch 1546/5000
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Epoch 1547/5000
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Epoch 1548/5000
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Epoch 1549/5000
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Epoch 1550/5000
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Epoch 1551/5000
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Epoch 1552/5000
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Epoch 1553/5000
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Epoch 1554/5000
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Epoch 1555/5000
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Epoch 1556/5000
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Epoch 1557/5000
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Epoch 1558/5000
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Epoch 1559/5000
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Epoch 1560/5000
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Epoch 1561/5000
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Epoch 1562/5000
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Epoch 1563/5000
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Epoch 1564/5000
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Epoch 1565/5000
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Epoch 1566/5000
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Epoch 1567/5000
10/10 - 0s - 9ms/step - loss: 7.7096e-09
Epoch 1568/5000
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Epoch 1569/5000
10/10 - 0s - 9ms/step - loss: 9.3699e-10
Epoch 1570/5000
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Epoch 1571/5000
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Epoch 1572/5000
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Epoch 1573/5000
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Epoch 1574/5000
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Epoch 1575/5000
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Epoch 1576/5000
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Epoch 1577/5000
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Epoch 1578/5000
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Epoch 1579/5000
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Epoch 1580/5000
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Epoch 1581/5000
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Epoch 1582/5000
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Epoch 1583/5000
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Epoch 1584/5000
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Epoch 1585/5000
10/10 - 0s - 9ms/step - loss: 8.5881e-09
Epoch 1586/5000
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Epoch 1587/5000
10/10 - 0s - 7ms/step - loss: 6.2874e-09
Epoch 1588/5000
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Epoch 1589/5000
10/10 - 0s - 9ms/step - loss: 4.9321e-09
Epoch 1590/5000
10/10 - 0s - 9ms/step - loss: 7.9055e-08
Epoch 1591/5000
10/10 - 0s - 9ms/step - loss: 3.2997e-07
Epoch 1592/5000
10/10 - 0s - 17ms/step - loss: 6.2980e-08
Epoch 1593/5000
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Epoch 1594/5000
10/10 - 0s - 15ms/step - loss: 9.0560e-09
Epoch 1595/5000
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Epoch 1596/5000
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Epoch 1597/5000
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Epoch 1598/5000
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Epoch 1599/5000
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Epoch 1600/5000
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Epoch 1601/5000
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Epoch 1602/5000
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Epoch 1603/5000
10/10 - 0s - 8ms/step - loss: 7.1531e-08
Epoch 1604/5000
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Epoch 1605/5000
10/10 - 0s - 8ms/step - loss: 8.4118e-09
Epoch 1606/5000
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Epoch 1607/5000
10/10 - 0s - 9ms/step - loss: 1.0025e-09
Epoch 1608/5000
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Epoch 1609/5000
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Epoch 1610/5000
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Epoch 1611/5000
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Epoch 1612/5000
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Epoch 1613/5000
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Epoch 1614/5000
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Epoch 1615/5000
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Epoch 1616/5000
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Epoch 1617/5000
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Epoch 1618/5000
10/10 - 0s - 8ms/step - loss: 9.2657e-10
Epoch 1619/5000
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Epoch 1620/5000
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Epoch 1621/5000
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Epoch 1622/5000
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Epoch 1623/5000
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Epoch 1624/5000
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Epoch 1625/5000
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Epoch 1626/5000
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Epoch 1627/5000
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Epoch 1628/5000
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Epoch 1629/5000
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Epoch 1630/5000
10/10 - 0s - 11ms/step - loss: 6.4809e-10
Epoch 1631/5000
10/10 - 0s - 8ms/step - loss: 4.7815e-11
Epoch 1632/5000
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Epoch 1633/5000
10/10 - 0s - 10ms/step - loss: 4.4364e-11
Epoch 1634/5000
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Epoch 1635/5000
10/10 - 0s - 8ms/step - loss: 6.6262e-10
Epoch 1636/5000
10/10 - 0s - 10ms/step - loss: 7.0087e-10
Epoch 1637/5000
10/10 - 0s - 9ms/step - loss: 8.5612e-09
Epoch 1638/5000
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Epoch 1639/5000
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Epoch 1640/5000
10/10 - 0s - 8ms/step - loss: 6.8002e-08
Epoch 1641/5000
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Epoch 1642/5000
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Epoch 1643/5000
10/10 - 0s - 10ms/step - loss: 7.0771e-09
Epoch 1644/5000
10/10 - 0s - 32ms/step - loss: 7.5019e-10
Epoch 1645/5000
10/10 - 0s - 20ms/step - loss: 2.2183e-09
Epoch 1646/5000
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Epoch 1647/5000
10/10 - 0s - 9ms/step - loss: 7.8746e-10
Epoch 1648/5000
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Epoch 1649/5000
10/10 - 0s - 8ms/step - loss: 2.1327e-07
Epoch 1650/5000
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Epoch 1651/5000
10/10 - 0s - 10ms/step - loss: 5.7878e-08
Epoch 1652/5000
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Epoch 1653/5000
10/10 - 0s - 8ms/step - loss: 9.3541e-09
Epoch 1654/5000
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Epoch 1655/5000
10/10 - 0s - 10ms/step - loss: 4.5310e-10
Epoch 1656/5000
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Epoch 1657/5000
10/10 - 0s - 9ms/step - loss: 7.2080e-10
Epoch 1658/5000
10/10 - 0s - 9ms/step - loss: 4.0217e-09
Epoch 1659/5000
10/10 - 0s - 9ms/step - loss: 8.8003e-08
Epoch 1660/5000
10/10 - 0s - 8ms/step - loss: 4.3429e-07
Epoch 1661/5000
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Epoch 1662/5000
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Epoch 1663/5000
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Epoch 1664/5000
10/10 - 0s - 9ms/step - loss: 6.7104e-09
Epoch 1665/5000
10/10 - 0s - 8ms/step - loss: 3.1038e-09
Epoch 1666/5000
10/10 - 0s - 9ms/step - loss: 1.2839e-09
Epoch 1667/5000
10/10 - 0s - 7ms/step - loss: 4.4340e-10
Epoch 1668/5000
10/10 - 0s - 8ms/step - loss: 1.2998e-10
Epoch 1669/5000
10/10 - 0s - 9ms/step - loss: 2.1913e-09
Epoch 1670/5000
10/10 - 0s - 9ms/step - loss: 1.3775e-09
Epoch 1671/5000
10/10 - 0s - 9ms/step - loss: 5.7658e-10
Epoch 1672/5000
10/10 - 0s - 9ms/step - loss: 2.8178e-10
Epoch 1673/5000
10/10 - 0s - 8ms/step - loss: 1.0300e-08
Epoch 1674/5000
10/10 - 0s - 9ms/step - loss: 2.7384e-07
Epoch 1675/5000
10/10 - 0s - 8ms/step - loss: 3.5728e-07
Epoch 1676/5000
10/10 - 0s - 9ms/step - loss: 1.1021e-07
Epoch 1677/5000
10/10 - 0s - 14ms/step - loss: 2.8033e-08
Epoch 1678/5000
10/10 - 0s - 12ms/step - loss: 1.5054e-08
Epoch 1679/5000
10/10 - 0s - 10ms/step - loss: 5.5414e-09
Epoch 1680/5000
10/10 - 0s - 8ms/step - loss: 2.0445e-09
Epoch 1681/5000
10/10 - 0s - 9ms/step - loss: 2.8604e-10
Epoch 1682/5000
10/10 - 0s - 9ms/step - loss: 8.8004e-10
Epoch 1683/5000
10/10 - 0s - 9ms/step - loss: 2.5597e-10
Epoch 1684/5000
10/10 - 0s - 9ms/step - loss: 5.6268e-11
Epoch 1685/5000
10/10 - 0s - 9ms/step - loss: 8.7594e-11
Epoch 1686/5000
10/10 - 0s - 10ms/step - loss: 3.8933e-10
Epoch 1687/5000
10/10 - 0s - 8ms/step - loss: 1.9350e-09
Epoch 1688/5000
10/10 - 0s - 8ms/step - loss: 4.4009e-09
Epoch 1689/5000
10/10 - 0s - 10ms/step - loss: 3.4107e-08
Epoch 1690/5000
10/10 - 0s - 8ms/step - loss: 3.1607e-07
Epoch 1691/5000
10/10 - 0s - 10ms/step - loss: 1.1895e-07
Epoch 1692/5000
10/10 - 0s - 9ms/step - loss: 4.1662e-08
Epoch 1693/5000
10/10 - 0s - 8ms/step - loss: 1.3616e-08
Epoch 1694/5000
10/10 - 0s - 9ms/step - loss: 5.2460e-09
Epoch 1695/5000
10/10 - 0s - 9ms/step - loss: 1.2423e-09
Epoch 1696/5000
10/10 - 0s - 9ms/step - loss: 1.0129e-09
Epoch 1697/5000
10/10 - 0s - 19ms/step - loss: 4.7191e-09
Epoch 1698/5000
10/10 - 0s - 32ms/step - loss: 6.6900e-10
Epoch 1699/5000
10/10 - 0s - 15ms/step - loss: 3.8962e-10
Epoch 1700/5000
10/10 - 0s - 9ms/step - loss: 9.7862e-10
Epoch 1701/5000
10/10 - 0s - 10ms/step - loss: 1.9004e-08
Epoch 1702/5000
10/10 - 0s - 19ms/step - loss: 5.3443e-07
Epoch 1703/5000
10/10 - 0s - 21ms/step - loss: 2.3755e-07
Epoch 1704/5000
10/10 - 0s - 33ms/step - loss: 7.3012e-08
Epoch 1705/5000
10/10 - 0s - 17ms/step - loss: 4.1076e-08
Epoch 1706/5000
10/10 - 0s - 10ms/step - loss: 9.9164e-09
Epoch 1707/5000
10/10 - 0s - 9ms/step - loss: 6.6831e-09
Epoch 1708/5000
10/10 - 0s - 10ms/step - loss: 1.7655e-09
Epoch 1709/5000
10/10 - 0s - 16ms/step - loss: 7.5848e-10
Epoch 1710/5000
10/10 - 0s - 9ms/step - loss: 7.0956e-10
Epoch 1711/5000
10/10 - 0s - 7ms/step - loss: 1.7077e-10
Epoch 1712/5000
10/10 - 0s - 8ms/step - loss: 4.5882e-11
Epoch 1713/5000
10/10 - 0s - 9ms/step - loss: 2.5673e-10
Epoch 1714/5000
10/10 - 0s - 9ms/step - loss: 2.6756e-10
Epoch 1715/5000
10/10 - 0s - 10ms/step - loss: 1.8518e-10
Epoch 1716/5000
10/10 - 0s - 9ms/step - loss: 2.5116e-10
Epoch 1717/5000
10/10 - 0s - 9ms/step - loss: 3.7934e-11
Epoch 1718/5000
10/10 - 0s - 9ms/step - loss: 2.9195e-11
Epoch 1719/5000
10/10 - 0s - 10ms/step - loss: 7.4184e-10
Epoch 1720/5000
10/10 - 0s - 8ms/step - loss: 2.6432e-08
Epoch 1721/5000
10/10 - 0s - 9ms/step - loss: 6.4293e-07
Epoch 1722/5000
10/10 - 0s - 9ms/step - loss: 2.0239e-07
Epoch 1723/5000
10/10 - 0s - 9ms/step - loss: 1.0882e-07
Epoch 1724/5000
10/10 - 0s - 9ms/step - loss: 2.4169e-08
Epoch 1725/5000
10/10 - 0s - 9ms/step - loss: 1.1739e-08
Epoch 1726/5000
10/10 - 0s - 7ms/step - loss: 2.2437e-09
Epoch 1727/5000
10/10 - 0s - 8ms/step - loss: 1.2893e-09
Epoch 1728/5000
10/10 - 0s - 9ms/step - loss: 4.2633e-10
Epoch 1729/5000
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Epoch 1730/5000
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Epoch 1731/5000
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Epoch 1732/5000
10/10 - 0s - 8ms/step - loss: 1.7174e-11
Epoch 1733/5000
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Epoch 1734/5000
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Epoch 1735/5000
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Epoch 1736/5000
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Epoch 1737/5000
10/10 - 0s - 10ms/step - loss: 1.0886e-10
Epoch 1738/5000
10/10 - 0s - 8ms/step - loss: 1.7473e-09
Epoch 1739/5000
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Epoch 1740/5000
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Epoch 1741/5000
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Epoch 1742/5000
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Epoch 1743/5000
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Epoch 1744/5000
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Epoch 1745/5000
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Epoch 1746/5000
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Epoch 1747/5000
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Epoch 1748/5000
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Epoch 1749/5000
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Epoch 1750/5000
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Epoch 1751/5000
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Epoch 1752/5000
10/10 - 0s - 10ms/step - loss: 3.9706e-08
Epoch 1753/5000
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Epoch 1754/5000
10/10 - 0s - 8ms/step - loss: 9.7940e-08
Epoch 1755/5000
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Epoch 1756/5000
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Epoch 1757/5000
10/10 - 0s - 9ms/step - loss: 7.1411e-09
Epoch 1758/5000
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Epoch 1759/5000
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Epoch 1760/5000
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Epoch 1761/5000
10/10 - 0s - 8ms/step - loss: 6.8743e-09
Epoch 1762/5000
10/10 - 0s - 9ms/step - loss: 1.0763e-08
Epoch 1763/5000
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Epoch 1764/5000
10/10 - 0s - 17ms/step - loss: 1.9786e-07
Epoch 1765/5000
10/10 - 0s - 8ms/step - loss: 1.8212e-07
Epoch 1766/5000
10/10 - 0s - 9ms/step - loss: 5.5320e-08
Epoch 1767/5000
10/10 - 0s - 9ms/step - loss: 1.7371e-08
Epoch 1768/5000
10/10 - 0s - 9ms/step - loss: 6.2666e-09
Epoch 1769/5000
10/10 - 0s - 9ms/step - loss: 3.0673e-09
Epoch 1770/5000
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Epoch 1771/5000
10/10 - 0s - 10ms/step - loss: 3.0777e-09
Epoch 1772/5000
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Epoch 1773/5000
10/10 - 0s - 9ms/step - loss: 9.7045e-10
Epoch 1774/5000
10/10 - 0s - 9ms/step - loss: 6.2797e-09
Epoch 1775/5000
10/10 - 0s - 8ms/step - loss: 1.7206e-07
Epoch 1776/5000
10/10 - 0s - 8ms/step - loss: 4.4903e-07
Epoch 1777/5000
10/10 - 0s - 8ms/step - loss: 1.5013e-07
Epoch 1778/5000
10/10 - 0s - 10ms/step - loss: 3.4122e-08
Epoch 1779/5000
10/10 - 0s - 8ms/step - loss: 1.2191e-08
Epoch 1780/5000
10/10 - 0s - 8ms/step - loss: 5.5447e-09
Epoch 1781/5000
10/10 - 0s - 9ms/step - loss: 1.1078e-09
Epoch 1782/5000
10/10 - 0s - 22ms/step - loss: 4.5674e-10
Epoch 1783/5000
10/10 - 0s - 9ms/step - loss: 2.6838e-10
Epoch 1784/5000
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Epoch 1785/5000
10/10 - 0s - 9ms/step - loss: 3.3389e-10
Epoch 1786/5000
10/10 - 0s - 9ms/step - loss: 6.1563e-11
Epoch 1787/5000
10/10 - 0s - 10ms/step - loss: 1.8417e-09
Epoch 1788/5000
10/10 - 0s - 8ms/step - loss: 8.9368e-10
Epoch 1789/5000
10/10 - 0s - 10ms/step - loss: 5.7570e-09
Epoch 1790/5000
10/10 - 0s - 9ms/step - loss: 1.5896e-08
Epoch 1791/5000
10/10 - 0s - 9ms/step - loss: 1.1619e-07
Epoch 1792/5000
10/10 - 0s - 9ms/step - loss: 2.1865e-07
Epoch 1793/5000
10/10 - 0s - 8ms/step - loss: 3.7031e-08
Epoch 1794/5000
10/10 - 0s - 7ms/step - loss: 9.9165e-09
Epoch 1795/5000
10/10 - 0s - 10ms/step - loss: 3.2709e-09
Epoch 1796/5000
10/10 - 0s - 9ms/step - loss: 4.4045e-09
Epoch 1797/5000
10/10 - 0s - 8ms/step - loss: 2.4070e-09
Epoch 1798/5000
10/10 - 0s - 8ms/step - loss: 9.1283e-10
Epoch 1799/5000
10/10 - 0s - 8ms/step - loss: 3.4164e-09
Epoch 1800/5000
10/10 - 0s - 9ms/step - loss: 1.1608e-07
Epoch 1801/5000
10/10 - 0s - 9ms/step - loss: 4.1032e-07
Epoch 1802/5000
10/10 - 0s - 10ms/step - loss: 1.1665e-07
Epoch 1803/5000
10/10 - 0s - 9ms/step - loss: 4.6998e-08
Epoch 1804/5000
10/10 - 0s - 10ms/step - loss: 1.4314e-08
Epoch 1805/5000
10/10 - 0s - 9ms/step - loss: 3.1976e-09
Epoch 1806/5000
10/10 - 0s - 18ms/step - loss: 1.3481e-09
Epoch 1807/5000
10/10 - 0s - 15ms/step - loss: 9.3613e-10
Epoch 1808/5000
10/10 - 0s - 17ms/step - loss: 1.4112e-09
Epoch 1809/5000
10/10 - 0s - 12ms/step - loss: 8.3636e-10
Epoch 1810/5000
10/10 - 0s - 9ms/step - loss: 2.6749e-09
Epoch 1811/5000
10/10 - 0s - 10ms/step - loss: 1.1274e-10
Epoch 1812/5000
10/10 - 0s - 19ms/step - loss: 2.9926e-09
Epoch 1813/5000
10/10 - 0s - 10ms/step - loss: 2.1909e-08
Epoch 1814/5000
10/10 - 0s - 9ms/step - loss: 1.1726e-07
Epoch 1815/5000
10/10 - 0s - 8ms/step - loss: 1.3861e-07
Epoch 1816/5000
10/10 - 0s - 10ms/step - loss: 3.4403e-08
Epoch 1817/5000
10/10 - 0s - 8ms/step - loss: 1.0218e-08
Epoch 1818/5000
10/10 - 0s - 11ms/step - loss: 1.4704e-08
Epoch 1819/5000
10/10 - 0s - 9ms/step - loss: 2.0176e-09
Epoch 1820/5000
10/10 - 0s - 10ms/step - loss: 1.5279e-09
Epoch 1821/5000
10/10 - 0s - 8ms/step - loss: 3.3571e-08
Epoch 1822/5000
10/10 - 0s - 10ms/step - loss: 2.8717e-07
Epoch 1823/5000
10/10 - 0s - 10ms/step - loss: 9.5319e-08
Epoch 1824/5000
10/10 - 0s - 17ms/step - loss: 3.4010e-08
Epoch 1825/5000
10/10 - 0s - 8ms/step - loss: 1.3933e-08
Epoch 1826/5000
10/10 - 0s - 8ms/step - loss: 9.9833e-09
Epoch 1827/5000
10/10 - 0s - 9ms/step - loss: 7.2250e-09
Epoch 1828/5000
10/10 - 0s - 8ms/step - loss: 1.2864e-09
Epoch 1829/5000
10/10 - 0s - 16ms/step - loss: 3.1689e-09
Epoch 1830/5000
10/10 - 0s - 9ms/step - loss: 1.9077e-10
Epoch 1831/5000
10/10 - 0s - 9ms/step - loss: 1.0869e-09
Epoch 1832/5000
10/10 - 0s - 8ms/step - loss: 5.2328e-08
Epoch 1833/5000
10/10 - 0s - 10ms/step - loss: 4.6420e-07
Epoch 1834/5000
10/10 - 0s - 17ms/step - loss: 1.0284e-07
Epoch 1835/5000
10/10 - 0s - 9ms/step - loss: 4.5046e-08
Epoch 1836/5000
10/10 - 0s - 10ms/step - loss: 2.0858e-08
Epoch 1837/5000
10/10 - 0s - 9ms/step - loss: 6.8783e-09
Epoch 1838/5000
10/10 - 0s - 9ms/step - loss: 2.2115e-09
Epoch 1839/5000
10/10 - 0s - 10ms/step - loss: 2.6865e-10
Epoch 1840/5000
10/10 - 0s - 9ms/step - loss: 2.1710e-11
Epoch 1841/5000
10/10 - 0s - 10ms/step - loss: 6.2489e-11
Epoch 1842/5000
10/10 - 0s - 16ms/step - loss: 8.4802e-10
Epoch 1843/5000
10/10 - 0s - 11ms/step - loss: 6.6674e-10
Epoch 1844/5000
10/10 - 0s - 17ms/step - loss: 3.9274e-10
Epoch 1845/5000
10/10 - 0s - 8ms/step - loss: 9.9972e-10
Epoch 1846/5000
10/10 - 0s - 8ms/step - loss: 1.1705e-08
Epoch 1847/5000
10/10 - 0s - 8ms/step - loss: 3.0081e-07
Epoch 1848/5000
10/10 - 0s - 10ms/step - loss: 2.8584e-07
Epoch 1849/5000
10/10 - 0s - 9ms/step - loss: 8.9489e-08
Epoch 1850/5000
10/10 - 0s - 8ms/step - loss: 2.5284e-08
Epoch 1851/5000
10/10 - 0s - 9ms/step - loss: 9.4143e-09
Epoch 1852/5000
10/10 - 0s - 11ms/step - loss: 5.6682e-09
Epoch 1853/5000
10/10 - 0s - 8ms/step - loss: 2.1383e-09
Epoch 1854/5000
10/10 - 0s - 18ms/step - loss: 7.8017e-10
Epoch 1855/5000
10/10 - 0s - 9ms/step - loss: 7.5983e-10
Epoch 1856/5000
10/10 - 0s - 8ms/step - loss: 9.4111e-10
Epoch 1857/5000
10/10 - 0s - 9ms/step - loss: 7.4955e-10
Epoch 1858/5000
10/10 - 0s - 8ms/step - loss: 3.2916e-09
Epoch 1859/5000
10/10 - 0s - 8ms/step - loss: 9.1998e-11
Epoch 1860/5000
10/10 - 0s - 10ms/step - loss: 1.4801e-09
Epoch 1861/5000
10/10 - 0s - 8ms/step - loss: 2.9599e-08
Epoch 1862/5000
10/10 - 0s - 10ms/step - loss: 3.5787e-07
Epoch 1863/5000
10/10 - 0s - 9ms/step - loss: 1.3832e-07
Epoch 1864/5000
10/10 - 0s - 9ms/step - loss: 5.1746e-08
Epoch 1865/5000
10/10 - 0s - 7ms/step - loss: 1.5601e-08
Epoch 1866/5000
10/10 - 0s - 9ms/step - loss: 6.5752e-09
Epoch 1867/5000
10/10 - 0s - 9ms/step - loss: 2.0902e-09
Epoch 1868/5000
10/10 - 0s - 10ms/step - loss: 1.5259e-09
Epoch 1869/5000
10/10 - 0s - 9ms/step - loss: 2.9199e-10
Epoch 1870/5000
10/10 - 0s - 7ms/step - loss: 9.2637e-10
Epoch 1871/5000
10/10 - 0s - 8ms/step - loss: 8.2211e-10
Epoch 1872/5000
10/10 - 0s - 7ms/step - loss: 1.5478e-09
Epoch 1873/5000
10/10 - 0s - 19ms/step - loss: 6.1586e-09
Epoch 1874/5000
10/10 - 0s - 9ms/step - loss: 4.5899e-08
Epoch 1875/5000
10/10 - 0s - 8ms/step - loss: 3.2162e-07
Epoch 1876/5000
10/10 - 0s - 18ms/step - loss: 1.0045e-07
Epoch 1877/5000
10/10 - 0s - 9ms/step - loss: 3.6050e-08
Epoch 1878/5000
10/10 - 0s - 10ms/step - loss: 1.4050e-08
Epoch 1879/5000
10/10 - 0s - 9ms/step - loss: 6.4709e-09
Epoch 1880/5000
10/10 - 0s - 9ms/step - loss: 1.7370e-09
Epoch 1881/5000
10/10 - 0s - 9ms/step - loss: 2.5822e-10
Epoch 1882/5000
10/10 - 0s - 8ms/step - loss: 1.0415e-09
Epoch 1883/5000
10/10 - 0s - 10ms/step - loss: 1.4614e-09
Epoch 1884/5000
10/10 - 0s - 8ms/step - loss: 4.0392e-10
Epoch 1885/5000
10/10 - 0s - 9ms/step - loss: 2.0350e-08
Epoch 1886/5000
10/10 - 0s - 8ms/step - loss: 3.5344e-07
Epoch 1887/5000
10/10 - 0s - 11ms/step - loss: 1.6665e-07
Epoch 1888/5000
10/10 - 0s - 9ms/step - loss: 5.2727e-08
Epoch 1889/5000
10/10 - 0s - 9ms/step - loss: 1.8282e-08
Epoch 1890/5000
10/10 - 0s - 8ms/step - loss: 9.0736e-09
Epoch 1891/5000
10/10 - 0s - 10ms/step - loss: 5.0041e-09
Epoch 1892/5000
10/10 - 0s - 9ms/step - loss: 3.6291e-09
Epoch 1893/5000
10/10 - 0s - 9ms/step - loss: 2.0792e-09
Epoch 1894/5000
10/10 - 0s - 10ms/step - loss: 3.7931e-10
Epoch 1895/5000
10/10 - 0s - 9ms/step - loss: 8.0197e-11
Epoch 1896/5000
10/10 - 0s - 8ms/step - loss: 6.6604e-10
Epoch 1897/5000
10/10 - 0s - 8ms/step - loss: 1.0245e-08
Epoch 1898/5000
10/10 - 0s - 9ms/step - loss: 8.9507e-08
Epoch 1899/5000
10/10 - 0s - 8ms/step - loss: 2.5274e-07
Epoch 1900/5000
10/10 - 0s - 9ms/step - loss: 5.1536e-08
Epoch 1901/5000
10/10 - 0s - 9ms/step - loss: 1.6185e-08
Epoch 1902/5000
10/10 - 0s - 9ms/step - loss: 4.8298e-09
Epoch 1903/5000
10/10 - 0s - 9ms/step - loss: 1.7856e-09
Epoch 1904/5000
10/10 - 0s - 9ms/step - loss: 3.4693e-10
Epoch 1905/5000
10/10 - 0s - 9ms/step - loss: 1.9856e-09
Epoch 1906/5000
10/10 - 0s - 8ms/step - loss: 2.0264e-08
Epoch 1907/5000
10/10 - 0s - 13ms/step - loss: 1.2539e-07
Epoch 1908/5000
10/10 - 0s - 19ms/step - loss: 1.4297e-07
Epoch 1909/5000
10/10 - 0s - 9ms/step - loss: 3.8210e-08
Epoch 1910/5000
10/10 - 0s - 9ms/step - loss: 7.0508e-09
Epoch 1911/5000
10/10 - 0s - 9ms/step - loss: 1.1657e-08
Epoch 1912/5000
10/10 - 0s - 8ms/step - loss: 1.0905e-09
Epoch 1913/5000
10/10 - 0s - 9ms/step - loss: 1.2740e-10
Epoch 1914/5000
10/10 - 0s - 9ms/step - loss: 6.3095e-09
Epoch 1915/5000
10/10 - 0s - 9ms/step - loss: 8.2000e-08
Epoch 1916/5000
10/10 - 0s - 19ms/step - loss: 3.5887e-07
Epoch 1917/5000
10/10 - 0s - 17ms/step - loss: 8.2109e-08
Epoch 1918/5000
10/10 - 0s - 16ms/step - loss: 3.1461e-08
Epoch 1919/5000
10/10 - 0s - 9ms/step - loss: 1.2820e-08
Epoch 1920/5000
10/10 - 0s - 10ms/step - loss: 5.0050e-09
Epoch 1921/5000
10/10 - 0s - 9ms/step - loss: 1.2358e-09
Epoch 1922/5000
10/10 - 0s - 9ms/step - loss: 5.8245e-10
Epoch 1923/5000
10/10 - 0s - 9ms/step - loss: 4.6144e-10
Epoch 1924/5000
10/10 - 0s - 9ms/step - loss: 4.1956e-09
Epoch 1925/5000
10/10 - 0s - 9ms/step - loss: 3.8591e-09
Epoch 1926/5000
10/10 - 0s - 8ms/step - loss: 6.0635e-09
Epoch 1927/5000
10/10 - 0s - 9ms/step - loss: 5.1876e-08
Epoch 1928/5000
10/10 - 0s - 10ms/step - loss: 3.4486e-07
Epoch 1929/5000
10/10 - 0s - 9ms/step - loss: 7.9889e-08
Epoch 1930/5000
10/10 - 0s - 9ms/step - loss: 2.8708e-08
Epoch 1931/5000
10/10 - 0s - 16ms/step - loss: 1.1569e-08
Epoch 1932/5000
10/10 - 0s - 9ms/step - loss: 6.3595e-09
Epoch 1933/5000
10/10 - 0s - 9ms/step - loss: 1.4345e-09
Epoch 1934/5000
10/10 - 0s - 9ms/step - loss: 4.2487e-10
Epoch 1935/5000
10/10 - 0s - 13ms/step - loss: 8.2404e-11
Epoch 1936/5000
10/10 - 0s - 11ms/step - loss: 7.9188e-10
Epoch 1937/5000
10/10 - 0s - 17ms/step - loss: 2.4696e-08
Epoch 1938/5000
10/10 - 0s - 10ms/step - loss: 1.4860e-07
Epoch 1939/5000
10/10 - 0s - 9ms/step - loss: 1.0099e-07
Epoch 1940/5000
10/10 - 0s - 8ms/step - loss: 2.6121e-08
Epoch 1941/5000
10/10 - 0s - 9ms/step - loss: 3.7020e-09
Epoch 1942/5000
10/10 - 0s - 8ms/step - loss: 1.9052e-09
Epoch 1943/5000
10/10 - 0s - 10ms/step - loss: 8.0903e-10
Epoch 1944/5000
10/10 - 0s - 8ms/step - loss: 3.1276e-09
Epoch 1945/5000
10/10 - 0s - 8ms/step - loss: 6.8558e-08
Epoch 1946/5000
10/10 - 0s - 10ms/step - loss: 3.5675e-07
Epoch 1947/5000
10/10 - 0s - 8ms/step - loss: 7.5806e-08
Epoch 1948/5000
10/10 - 0s - 8ms/step - loss: 2.8674e-08
Epoch 1949/5000
10/10 - 0s - 8ms/step - loss: 1.1727e-08
Epoch 1950/5000
10/10 - 0s - 11ms/step - loss: 4.4652e-09
Epoch 1951/5000
10/10 - 0s - 8ms/step - loss: 3.6390e-09
Epoch 1952/5000
10/10 - 0s - 9ms/step - loss: 1.1225e-09
Epoch 1953/5000
10/10 - 0s - 8ms/step - loss: 3.8154e-09
Epoch 1954/5000
10/10 - 0s - 9ms/step - loss: 8.5814e-10
Epoch 1955/5000
10/10 - 0s - 10ms/step - loss: 1.1860e-11
Epoch 1956/5000
10/10 - 0s - 18ms/step - loss: 6.1988e-10
Epoch 1957/5000
10/10 - 0s - 9ms/step - loss: 1.9592e-08
Epoch 1958/5000
10/10 - 0s - 9ms/step - loss: 4.4353e-07
Epoch 1959/5000
10/10 - 0s - 9ms/step - loss: 1.9170e-07
Epoch 1960/5000
10/10 - 0s - 9ms/step - loss: 4.8805e-08
Epoch 1961/5000
10/10 - 0s - 9ms/step - loss: 2.4211e-08
Epoch 1962/5000
10/10 - 0s - 9ms/step - loss: 1.2511e-08
Epoch 1963/5000
10/10 - 0s - 8ms/step - loss: 4.5812e-09
Epoch 1964/5000
10/10 - 0s - 8ms/step - loss: 1.6546e-09
Epoch 1965/5000
10/10 - 0s - 10ms/step - loss: 7.7964e-10
Epoch 1966/5000
10/10 - 0s - 9ms/step - loss: 1.8352e-10
Epoch 1967/5000
10/10 - 0s - 18ms/step - loss: 1.4154e-10
Epoch 1968/5000
10/10 - 0s - 13ms/step - loss: 8.3339e-10
Epoch 1969/5000
10/10 - 0s - 17ms/step - loss: 2.5135e-10
Epoch 1970/5000
10/10 - 0s - 8ms/step - loss: 2.9562e-11
Epoch 1971/5000
10/10 - 0s - 9ms/step - loss: 2.5968e-09
Epoch 1972/5000
10/10 - 0s - 8ms/step - loss: 4.2055e-08
Epoch 1973/5000
10/10 - 0s - 10ms/step - loss: 3.0660e-07
Epoch 1974/5000
10/10 - 0s - 16ms/step - loss: 8.1592e-08
Epoch 1975/5000
10/10 - 0s - 17ms/step - loss: 3.3892e-08
Epoch 1976/5000
10/10 - 0s - 8ms/step - loss: 1.2343e-08
Epoch 1977/5000
10/10 - 0s - 10ms/step - loss: 4.0063e-09
Epoch 1978/5000
10/10 - 0s - 10ms/step - loss: 6.5640e-10
Epoch 1979/5000
10/10 - 0s - 8ms/step - loss: 1.4869e-10
Epoch 1980/5000
10/10 - 0s - 10ms/step - loss: 3.3023e-11
Epoch 1981/5000
10/10 - 0s - 9ms/step - loss: 1.6804e-11
Epoch 1982/5000
10/10 - 0s - 8ms/step - loss: 3.4255e-10
Epoch 1983/5000
10/10 - 0s - 8ms/step - loss: 1.8462e-09
Epoch 1984/5000
10/10 - 0s - 9ms/step - loss: 4.7397e-08
Epoch 1985/5000
10/10 - 0s - 8ms/step - loss: 6.4550e-07
Epoch 1986/5000
10/10 - 0s - 10ms/step - loss: 1.7015e-07
Epoch 1987/5000
10/10 - 0s - 9ms/step - loss: 6.9678e-08
Epoch 1988/5000
10/10 - 0s - 9ms/step - loss: 1.8689e-08
Epoch 1989/5000
10/10 - 0s - 10ms/step - loss: 6.7244e-09
Epoch 1990/5000
10/10 - 0s - 9ms/step - loss: 3.5801e-09
Epoch 1991/5000
10/10 - 0s - 10ms/step - loss: 1.3850e-09
Epoch 1992/5000
10/10 - 0s - 10ms/step - loss: 2.9711e-10
Epoch 1993/5000
10/10 - 0s - 8ms/step - loss: 3.4954e-10
Epoch 1994/5000
10/10 - 0s - 10ms/step - loss: 2.9826e-10
Epoch 1995/5000
10/10 - 0s - 9ms/step - loss: 3.4839e-10
Epoch 1996/5000
10/10 - 0s - 10ms/step - loss: 4.8571e-10
Epoch 1997/5000
10/10 - 0s - 9ms/step - loss: 2.2701e-10
Epoch 1998/5000
10/10 - 0s - 10ms/step - loss: 5.0612e-10
Epoch 1999/5000
10/10 - 0s - 9ms/step - loss: 1.0023e-10
Epoch 2000/5000
10/10 - 0s - 9ms/step - loss: 7.7755e-10
Epoch 2001/5000
10/10 - 0s - 12ms/step - loss: 4.1555e-09
Epoch 2002/5000
10/10 - 0s - 14ms/step - loss: 4.4695e-09
Epoch 2003/5000
10/10 - 0s - 11ms/step - loss: 7.4760e-09
Epoch 2004/5000
10/10 - 0s - 9ms/step - loss: 1.9996e-07
Epoch 2005/5000
10/10 - 0s - 9ms/step - loss: 4.3729e-07
Epoch 2006/5000
10/10 - 0s - 18ms/step - loss: 1.3724e-07
Epoch 2007/5000
10/10 - 0s - 10ms/step - loss: 3.0071e-08
Epoch 2008/5000
10/10 - 0s - 9ms/step - loss: 1.9355e-08
Epoch 2009/5000
10/10 - 0s - 18ms/step - loss: 5.0443e-09
Epoch 2010/5000
10/10 - 0s - 8ms/step - loss: 1.2765e-09
Epoch 2011/5000
10/10 - 0s - 9ms/step - loss: 1.1664e-09
Epoch 2012/5000
10/10 - 0s - 8ms/step - loss: 5.9556e-10
Epoch 2013/5000
10/10 - 0s - 9ms/step - loss: 6.6821e-10
Epoch 2014/5000
10/10 - 0s - 8ms/step - loss: 4.0222e-10
Epoch 2015/5000
10/10 - 0s - 8ms/step - loss: 2.3186e-10
Epoch 2016/5000
10/10 - 0s - 10ms/step - loss: 4.9081e-09
Epoch 2017/5000
10/10 - 0s - 10ms/step - loss: 2.0770e-09
Epoch 2018/5000
10/10 - 0s - 9ms/step - loss: 2.1122e-10
Epoch 2019/5000
10/10 - 0s - 10ms/step - loss: 1.9138e-09
Epoch 2020/5000
10/10 - 0s - 9ms/step - loss: 1.0661e-08
Epoch 2021/5000
10/10 - 0s - 10ms/step - loss: 1.9939e-07
Epoch 2022/5000
10/10 - 0s - 9ms/step - loss: 2.5530e-07
Epoch 2023/5000
10/10 - 0s - 8ms/step - loss: 8.4278e-08
Epoch 2024/5000
10/10 - 0s - 10ms/step - loss: 2.9679e-08
Epoch 2025/5000
10/10 - 0s - 8ms/step - loss: 1.1184e-08
Epoch 2026/5000
10/10 - 0s - 9ms/step - loss: 3.5141e-09
Epoch 2027/5000
10/10 - 0s - 9ms/step - loss: 1.5903e-09
Epoch 2028/5000
10/10 - 0s - 18ms/step - loss: 8.8500e-10
Epoch 2029/5000
10/10 - 0s - 9ms/step - loss: 6.0784e-10
Epoch 2030/5000
10/10 - 0s - 9ms/step - loss: 6.5317e-11
Epoch 2031/5000
10/10 - 0s - 9ms/step - loss: 6.7025e-10
Epoch 2032/5000
10/10 - 0s - 9ms/step - loss: 1.4823e-08
Epoch 2033/5000
10/10 - 0s - 10ms/step - loss: 1.5226e-07
Epoch 2034/5000
10/10 - 0s - 10ms/step - loss: 1.5885e-07
Epoch 2035/5000
10/10 - 0s - 8ms/step - loss: 5.1214e-08
Epoch 2036/5000
10/10 - 0s - 10ms/step - loss: 1.7985e-08
Epoch 2037/5000
10/10 - 0s - 9ms/step - loss: 7.4657e-09
Epoch 2038/5000
10/10 - 0s - 9ms/step - loss: 3.9968e-09
Epoch 2039/5000
10/10 - 0s - 22ms/step - loss: 5.2564e-09
Epoch 2040/5000
10/10 - 0s - 21ms/step - loss: 5.5007e-09
Epoch 2041/5000
10/10 - 0s - 17ms/step - loss: 1.1444e-08
Epoch 2042/5000
10/10 - 0s - 9ms/step - loss: 1.0180e-07
Epoch 2043/5000
10/10 - 0s - 9ms/step - loss: 2.4691e-07
Epoch 2044/5000
10/10 - 0s - 9ms/step - loss: 6.5679e-08
Epoch 2045/5000
10/10 - 0s - 9ms/step - loss: 2.5823e-08
Epoch 2046/5000
10/10 - 0s - 10ms/step - loss: 1.1235e-08
Epoch 2047/5000
10/10 - 0s - 9ms/step - loss: 3.7006e-09
Epoch 2048/5000
10/10 - 0s - 9ms/step - loss: 1.6049e-09
Epoch 2049/5000
10/10 - 0s - 10ms/step - loss: 3.1730e-09
Epoch 2050/5000
10/10 - 0s - 9ms/step - loss: 5.3806e-10
Epoch 2051/5000
10/10 - 0s - 8ms/step - loss: 6.8258e-10
Epoch 2052/5000
10/10 - 0s - 9ms/step - loss: 2.1522e-08
Epoch 2053/5000
10/10 - 0s - 9ms/step - loss: 3.3229e-07
Epoch 2054/5000
10/10 - 0s - 11ms/step - loss: 1.5501e-07
Epoch 2055/5000
10/10 - 0s - 9ms/step - loss: 5.2147e-08
Epoch 2056/5000
10/10 - 0s - 8ms/step - loss: 1.8042e-08
Epoch 2057/5000
10/10 - 0s - 8ms/step - loss: 5.3695e-09
Epoch 2058/5000
10/10 - 0s - 9ms/step - loss: 1.8224e-09
Epoch 2059/5000
10/10 - 0s - 8ms/step - loss: 1.0072e-09
Epoch 2060/5000
10/10 - 0s - 9ms/step - loss: 5.7728e-11
Epoch 2061/5000
10/10 - 0s - 9ms/step - loss: 1.2561e-10
Epoch 2062/5000
10/10 - 0s - 9ms/step - loss: 1.4007e-10
Epoch 2063/5000
10/10 - 0s - 8ms/step - loss: 2.8479e-11
Epoch 2064/5000
10/10 - 0s - 8ms/step - loss: 5.1406e-10
Epoch 2065/5000
10/10 - 0s - 9ms/step - loss: 5.9965e-09
Epoch 2066/5000
10/10 - 0s - 8ms/step - loss: 1.6551e-07
Epoch 2067/5000
10/10 - 0s - 8ms/step - loss: 4.1926e-07
Epoch 2068/5000
10/10 - 0s - 9ms/step - loss: 1.3259e-07
Epoch 2069/5000
10/10 - 0s - 8ms/step - loss: 3.5414e-08
Epoch 2070/5000
10/10 - 0s - 10ms/step - loss: 1.1359e-08
Epoch 2071/5000
10/10 - 0s - 9ms/step - loss: 6.7140e-09
Epoch 2072/5000
10/10 - 0s - 7ms/step - loss: 2.2106e-09
Epoch 2073/5000
10/10 - 0s - 11ms/step - loss: 2.0533e-09
Epoch 2074/5000
10/10 - 0s - 9ms/step - loss: 7.3277e-10
Epoch 2075/5000
10/10 - 0s - 9ms/step - loss: 6.9839e-10
Epoch 2076/5000
10/10 - 0s - 9ms/step - loss: 1.8648e-10
Epoch 2077/5000
10/10 - 0s - 9ms/step - loss: 2.9864e-10
Epoch 2078/5000
10/10 - 0s - 9ms/step - loss: 1.4158e-09
Epoch 2079/5000
10/10 - 0s - 9ms/step - loss: 4.0795e-10
Epoch 2080/5000
10/10 - 0s - 8ms/step - loss: 5.9559e-09
Epoch 2081/5000
10/10 - 0s - 13ms/step - loss: 6.7666e-08
Epoch 2082/5000
10/10 - 0s - 15ms/step - loss: 2.9665e-07
Epoch 2083/5000
10/10 - 0s - 11ms/step - loss: 6.3414e-08
Epoch 2084/5000
10/10 - 0s - 8ms/step - loss: 2.6496e-08
Epoch 2085/5000
10/10 - 0s - 8ms/step - loss: 1.0882e-08
Epoch 2086/5000
10/10 - 0s - 10ms/step - loss: 5.0193e-09
Epoch 2087/5000
10/10 - 0s - 9ms/step - loss: 2.3964e-09
Epoch 2088/5000
10/10 - 0s - 8ms/step - loss: 3.8304e-09
Epoch 2089/5000
10/10 - 0s - 8ms/step - loss: 2.4221e-09
Epoch 2090/5000
10/10 - 0s - 10ms/step - loss: 1.4509e-09
Epoch 2091/5000
10/10 - 0s - 9ms/step - loss: 2.1784e-08
Epoch 2092/5000
10/10 - 0s - 9ms/step - loss: 1.8264e-07
Epoch 2093/5000
10/10 - 0s - 8ms/step - loss: 1.5091e-07
Epoch 2094/5000
10/10 - 0s - 8ms/step - loss: 5.4105e-08
Epoch 2095/5000
10/10 - 0s - 9ms/step - loss: 1.2326e-08
Epoch 2096/5000
10/10 - 0s - 8ms/step - loss: 4.7459e-09
Epoch 2097/5000
10/10 - 0s - 10ms/step - loss: 2.4607e-09
Epoch 2098/5000
10/10 - 0s - 8ms/step - loss: 6.0697e-09
Epoch 2099/5000
10/10 - 0s - 9ms/step - loss: 1.0935e-08
Epoch 2100/5000
10/10 - 0s - 9ms/step - loss: 7.7494e-09
Epoch 2101/5000
10/10 - 0s - 9ms/step - loss: 1.0256e-08
Epoch 2102/5000
10/10 - 0s - 10ms/step - loss: 7.1883e-08
Epoch 2103/5000
10/10 - 0s - 9ms/step - loss: 3.7950e-07
Epoch 2104/5000
10/10 - 0s - 8ms/step - loss: 8.0993e-08
Epoch 2105/5000
10/10 - 0s - 9ms/step - loss: 2.7876e-08
Epoch 2106/5000
10/10 - 0s - 9ms/step - loss: 1.4102e-08
Epoch 2107/5000
10/10 - 0s - 9ms/step - loss: 5.1613e-09
Epoch 2108/5000
10/10 - 0s - 8ms/step - loss: 1.0336e-09
Epoch 2109/5000
10/10 - 0s - 9ms/step - loss: 2.4847e-10
Epoch 2110/5000
10/10 - 0s - 9ms/step - loss: 9.5051e-10
Epoch 2111/5000
10/10 - 0s - 9ms/step - loss: 2.2406e-10
Epoch 2112/5000
10/10 - 0s - 7ms/step - loss: 6.1226e-11
Epoch 2113/5000
10/10 - 0s - 9ms/step - loss: 1.0962e-10
Epoch 2114/5000
10/10 - 0s - 8ms/step - loss: 8.5397e-11
Epoch 2115/5000
10/10 - 0s - 8ms/step - loss: 1.3463e-08
Epoch 2116/5000
10/10 - 0s - 8ms/step - loss: 4.4648e-07
Epoch 2117/5000
10/10 - 0s - 9ms/step - loss: 2.7212e-07
Epoch 2118/5000
10/10 - 0s - 9ms/step - loss: 5.7686e-08
Epoch 2119/5000
10/10 - 0s - 10ms/step - loss: 3.5996e-08
Epoch 2120/5000
10/10 - 0s - 10ms/step - loss: 9.5166e-09
Epoch 2121/5000
10/10 - 0s - 10ms/step - loss: 4.2995e-09
Epoch 2122/5000
10/10 - 0s - 8ms/step - loss: 1.4215e-09
Epoch 2123/5000
10/10 - 0s - 8ms/step - loss: 3.2198e-10
Epoch 2124/5000
10/10 - 0s - 8ms/step - loss: 2.8687e-10
Epoch 2125/5000
10/10 - 0s - 9ms/step - loss: 2.9808e-10
Epoch 2126/5000
10/10 - 0s - 8ms/step - loss: 4.5180e-10
Epoch 2127/5000
10/10 - 0s - 10ms/step - loss: 1.5714e-10
Epoch 2128/5000
10/10 - 0s - 9ms/step - loss: 4.0389e-10
Epoch 2129/5000
10/10 - 0s - 8ms/step - loss: 8.6642e-10
Epoch 2130/5000
10/10 - 0s - 10ms/step - loss: 1.4646e-09
Epoch 2131/5000
10/10 - 0s - 10ms/step - loss: 2.8657e-09
Epoch 2132/5000
10/10 - 0s - 9ms/step - loss: 1.6814e-08
Epoch 2133/5000
10/10 - 0s - 9ms/step - loss: 2.6798e-07
Epoch 2134/5000
10/10 - 0s - 10ms/step - loss: 1.9210e-07
Epoch 2135/5000
10/10 - 0s - 9ms/step - loss: 6.6206e-08
Epoch 2136/5000
10/10 - 0s - 10ms/step - loss: 2.1574e-08
Epoch 2137/5000
10/10 - 0s - 21ms/step - loss: 6.9653e-09
Epoch 2138/5000
10/10 - 0s - 8ms/step - loss: 1.9138e-09
Epoch 2139/5000
10/10 - 0s - 7ms/step - loss: 4.2030e-10
Epoch 2140/5000
10/10 - 0s - 8ms/step - loss: 2.0272e-11
Epoch 2141/5000
10/10 - 0s - 10ms/step - loss: 1.8431e-10
Epoch 2142/5000
10/10 - 0s - 10ms/step - loss: 4.7121e-09
Epoch 2143/5000
10/10 - 0s - 8ms/step - loss: 3.3057e-08
Epoch 2144/5000
10/10 - 0s - 10ms/step - loss: 1.2166e-07
Epoch 2145/5000
10/10 - 0s - 9ms/step - loss: 5.8482e-08
Epoch 2146/5000
10/10 - 0s - 8ms/step - loss: 2.8012e-08
Epoch 2147/5000
10/10 - 0s - 9ms/step - loss: 1.1157e-08
Epoch 2148/5000
10/10 - 0s - 9ms/step - loss: 7.2140e-10
Epoch 2149/5000
10/10 - 0s - 9ms/step - loss: 5.1715e-09
Epoch 2150/5000
10/10 - 0s - 8ms/step - loss: 1.9263e-08
Epoch 2151/5000
10/10 - 0s - 8ms/step - loss: 2.5896e-07
Epoch 2152/5000
10/10 - 0s - 10ms/step - loss: 2.0756e-07
Epoch 2153/5000
10/10 - 0s - 9ms/step - loss: 6.6055e-08
Epoch 2154/5000
10/10 - 0s - 10ms/step - loss: 2.1372e-08
Epoch 2155/5000
10/10 - 0s - 8ms/step - loss: 6.8639e-09
Epoch 2156/5000
10/10 - 0s - 7ms/step - loss: 3.0084e-09
Epoch 2157/5000
10/10 - 0s - 9ms/step - loss: 9.1926e-10
Epoch 2158/5000
10/10 - 0s - 8ms/step - loss: 2.6528e-10
Epoch 2159/5000
10/10 - 0s - 9ms/step - loss: 1.7108e-10
Epoch 2160/5000
10/10 - 0s - 8ms/step - loss: 1.9067e-09
Epoch 2161/5000
10/10 - 0s - 8ms/step - loss: 1.8653e-09
Epoch 2162/5000
10/10 - 0s - 9ms/step - loss: 2.8628e-09
Epoch 2163/5000
10/10 - 0s - 8ms/step - loss: 6.2711e-08
Epoch 2164/5000
10/10 - 0s - 9ms/step - loss: 3.4833e-07
Epoch 2165/5000
10/10 - 0s - 8ms/step - loss: 7.7983e-08
Epoch 2166/5000
10/10 - 0s - 8ms/step - loss: 2.3289e-08
Epoch 2167/5000
10/10 - 0s - 9ms/step - loss: 6.8293e-09
Epoch 2168/5000
10/10 - 0s - 9ms/step - loss: 1.5152e-09
Epoch 2169/5000
10/10 - 0s - 10ms/step - loss: 1.1562e-09
Epoch 2170/5000
10/10 - 0s - 9ms/step - loss: 7.0972e-10
Epoch 2171/5000
10/10 - 0s - 12ms/step - loss: 6.1005e-09
Epoch 2172/5000
10/10 - 0s - 12ms/step - loss: 7.0679e-09
Epoch 2173/5000
10/10 - 0s - 16ms/step - loss: 5.5863e-10
Epoch 2174/5000
10/10 - 0s - 9ms/step - loss: 1.5232e-08
Epoch 2175/5000
10/10 - 0s - 9ms/step - loss: 2.0593e-07
Epoch 2176/5000
10/10 - 0s - 9ms/step - loss: 1.6926e-07
Epoch 2177/5000
10/10 - 0s - 8ms/step - loss: 6.0173e-08
Epoch 2178/5000
10/10 - 0s - 8ms/step - loss: 2.3351e-08
Epoch 2179/5000
10/10 - 0s - 9ms/step - loss: 1.0627e-08
Epoch 2180/5000
10/10 - 0s - 10ms/step - loss: 2.3279e-09
Epoch 2181/5000
10/10 - 0s - 9ms/step - loss: 2.4226e-09
Epoch 2182/5000
10/10 - 0s - 9ms/step - loss: 8.4450e-10
Epoch 2183/5000
10/10 - 0s - 10ms/step - loss: 4.3474e-10
Epoch 2184/5000
10/10 - 0s - 10ms/step - loss: 6.2804e-10
Epoch 2185/5000
10/10 - 0s - 9ms/step - loss: 2.4065e-08
Epoch 2186/5000
10/10 - 0s - 9ms/step - loss: 3.0484e-07
Epoch 2187/5000
10/10 - 0s - 9ms/step - loss: 1.3612e-07
Epoch 2188/5000
10/10 - 0s - 10ms/step - loss: 4.6218e-08
Epoch 2189/5000
10/10 - 0s - 8ms/step - loss: 1.7832e-08
Epoch 2190/5000
10/10 - 0s - 8ms/step - loss: 6.3675e-09
Epoch 2191/5000
10/10 - 0s - 10ms/step - loss: 1.7968e-09
Epoch 2192/5000
10/10 - 0s - 8ms/step - loss: 3.5293e-10
Epoch 2193/5000
10/10 - 0s - 8ms/step - loss: 8.0761e-10
Epoch 2194/5000
10/10 - 0s - 9ms/step - loss: 1.4081e-09
Epoch 2195/5000
10/10 - 0s - 9ms/step - loss: 9.2734e-09
Epoch 2196/5000
10/10 - 0s - 9ms/step - loss: 5.0674e-08
Epoch 2197/5000
10/10 - 0s - 9ms/step - loss: 1.5297e-07
Epoch 2198/5000
10/10 - 0s - 8ms/step - loss: 3.2112e-08
Epoch 2199/5000
10/10 - 0s - 9ms/step - loss: 4.2466e-08
Epoch 2200/5000
10/10 - 0s - 9ms/step - loss: 4.2303e-09
Epoch 2201/5000
10/10 - 0s - 10ms/step - loss: 7.6210e-09
Epoch 2202/5000
10/10 - 0s - 9ms/step - loss: 2.4651e-08
Epoch 2203/5000
10/10 - 0s - 7ms/step - loss: 7.1437e-08
Epoch 2204/5000
10/10 - 0s - 10ms/step - loss: 1.0969e-07
Epoch 2205/5000
10/10 - 0s - 9ms/step - loss: 1.4548e-08
Epoch 2206/5000
10/10 - 0s - 8ms/step - loss: 7.0645e-09
Epoch 2207/5000
10/10 - 0s - 8ms/step - loss: 3.2310e-08
Epoch 2208/5000
10/10 - 0s - 10ms/step - loss: 8.8426e-08
Epoch 2209/5000
10/10 - 0s - 10ms/step - loss: 7.5030e-08
Epoch 2210/5000
10/10 - 0s - 9ms/step - loss: 6.6136e-09
Epoch 2211/5000
10/10 - 0s - 8ms/step - loss: 2.7216e-08
Epoch 2212/5000
10/10 - 0s - 20ms/step - loss: 3.7135e-08
Epoch 2213/5000
10/10 - 0s - 10ms/step - loss: 7.9778e-08
Epoch 2214/5000
10/10 - 0s - 8ms/step - loss: 5.6016e-08
Epoch 2215/5000
10/10 - 0s - 10ms/step - loss: 6.0201e-09
Epoch 2216/5000
10/10 - 0s - 8ms/step - loss: 3.9360e-09
Epoch 2217/5000
10/10 - 0s - 10ms/step - loss: 6.0484e-08
Epoch 2218/5000
10/10 - 0s - 9ms/step - loss: 2.3179e-07
Epoch 2219/5000
10/10 - 0s - 9ms/step - loss: 3.8291e-08
Epoch 2220/5000
10/10 - 0s - 9ms/step - loss: 1.2950e-08
Epoch 2221/5000
10/10 - 0s - 10ms/step - loss: 8.6417e-09
Epoch 2222/5000
10/10 - 0s - 8ms/step - loss: 1.1815e-08
Epoch 2223/5000
10/10 - 0s - 9ms/step - loss: 7.8942e-09
Epoch 2224/5000
10/10 - 0s - 8ms/step - loss: 8.6687e-09
Epoch 2225/5000
10/10 - 0s - 7ms/step - loss: 5.7001e-08
Epoch 2226/5000
10/10 - 0s - 9ms/step - loss: 1.1750e-07
Epoch 2227/5000
10/10 - 0s - 7ms/step - loss: 2.9873e-08
Epoch 2228/5000
10/10 - 0s - 10ms/step - loss: 2.9558e-08
Epoch 2229/5000
10/10 - 0s - 9ms/step - loss: 3.0115e-08
Epoch 2230/5000
10/10 - 0s - 8ms/step - loss: 3.0681e-09
Epoch 2231/5000
10/10 - 0s - 9ms/step - loss: 6.6002e-09
Epoch 2232/5000
10/10 - 0s - 9ms/step - loss: 8.4010e-08
Epoch 2233/5000
10/10 - 0s - 8ms/step - loss: 2.5667e-07
Epoch 2234/5000
10/10 - 0s - 9ms/step - loss: 5.7540e-08
Epoch 2235/5000
10/10 - 0s - 17ms/step - loss: 2.0163e-08
Epoch 2236/5000
10/10 - 0s - 9ms/step - loss: 6.7747e-09
Epoch 2237/5000
10/10 - 0s - 10ms/step - loss: 1.8287e-09
Epoch 2238/5000
10/10 - 0s - 18ms/step - loss: 2.4522e-09
Epoch 2239/5000
10/10 - 0s - 17ms/step - loss: 3.0270e-09
Epoch 2240/5000
10/10 - 0s - 9ms/step - loss: 4.6476e-09
Epoch 2241/5000
10/10 - 0s - 9ms/step - loss: 4.5822e-08
Epoch 2242/5000
10/10 - 0s - 10ms/step - loss: 2.3275e-07
Epoch 2243/5000
10/10 - 0s - 9ms/step - loss: 5.2435e-08
Epoch 2244/5000
10/10 - 0s - 9ms/step - loss: 2.6052e-08
Epoch 2245/5000
10/10 - 0s - 9ms/step - loss: 1.3285e-08
Epoch 2246/5000
10/10 - 0s - 8ms/step - loss: 1.8409e-09
Epoch 2247/5000
10/10 - 0s - 7ms/step - loss: 1.5552e-09
Epoch 2248/5000
10/10 - 0s - 9ms/step - loss: 3.2580e-10
Epoch 2249/5000
10/10 - 0s - 9ms/step - loss: 4.3995e-09
Epoch 2250/5000
10/10 - 0s - 8ms/step - loss: 7.4497e-08
Epoch 2251/5000
10/10 - 0s - 10ms/step - loss: 3.3323e-07
Epoch 2252/5000
10/10 - 0s - 9ms/step - loss: 7.8821e-08
Epoch 2253/5000
10/10 - 0s - 8ms/step - loss: 2.8018e-08
Epoch 2254/5000
10/10 - 0s - 9ms/step - loss: 1.0273e-08
Epoch 2255/5000
10/10 - 0s - 7ms/step - loss: 2.9898e-09
Epoch 2256/5000
10/10 - 0s - 8ms/step - loss: 6.5006e-10
Epoch 2257/5000
10/10 - 0s - 8ms/step - loss: 1.7285e-09
Epoch 2258/5000
10/10 - 0s - 9ms/step - loss: 2.1489e-09
Epoch 2259/5000
10/10 - 0s - 8ms/step - loss: 1.2761e-10
Epoch 2260/5000
10/10 - 0s - 8ms/step - loss: 7.9686e-10
Epoch 2261/5000
10/10 - 0s - 13ms/step - loss: 1.8813e-09
Epoch 2262/5000
10/10 - 0s - 13ms/step - loss: 3.7986e-09
Epoch 2263/5000
10/10 - 0s - 11ms/step - loss: 1.0297e-07
Epoch 2264/5000
10/10 - 0s - 8ms/step - loss: 5.0877e-07
Epoch 2265/5000
10/10 - 0s - 8ms/step - loss: 1.7068e-07
Epoch 2266/5000
10/10 - 0s - 8ms/step - loss: 4.5502e-08
Epoch 2267/5000
10/10 - 0s - 9ms/step - loss: 1.5952e-08
Epoch 2268/5000
10/10 - 0s - 9ms/step - loss: 7.2094e-09
Epoch 2269/5000
10/10 - 0s - 7ms/step - loss: 1.6563e-09
Epoch 2270/5000
10/10 - 0s - 8ms/step - loss: 5.3962e-10
Epoch 2271/5000
10/10 - 0s - 9ms/step - loss: 6.4904e-11
Epoch 2272/5000
10/10 - 0s - 10ms/step - loss: 1.6258e-10
Epoch 2273/5000
10/10 - 0s - 9ms/step - loss: 3.2056e-11
Epoch 2274/5000
10/10 - 0s - 9ms/step - loss: 8.5921e-11
Epoch 2275/5000
10/10 - 0s - 9ms/step - loss: 5.4618e-10
Epoch 2276/5000
10/10 - 0s - 9ms/step - loss: 2.9506e-10
Epoch 2277/5000
10/10 - 0s - 9ms/step - loss: 3.5048e-10
Epoch 2278/5000
10/10 - 0s - 8ms/step - loss: 5.2951e-09
Epoch 2279/5000
10/10 - 0s - 9ms/step - loss: 2.1075e-08
Epoch 2280/5000
10/10 - 0s - 9ms/step - loss: 1.3313e-07
Epoch 2281/5000
10/10 - 0s - 9ms/step - loss: 1.2606e-07
Epoch 2282/5000
10/10 - 0s - 9ms/step - loss: 2.4308e-08
Epoch 2283/5000
10/10 - 0s - 9ms/step - loss: 3.1806e-09
Epoch 2284/5000
10/10 - 0s - 9ms/step - loss: 2.0905e-09
Epoch 2285/5000
10/10 - 0s - 8ms/step - loss: 4.5859e-09
Epoch 2286/5000
10/10 - 0s - 8ms/step - loss: 1.2201e-08
Epoch 2287/5000
10/10 - 0s - 9ms/step - loss: 6.5490e-08
Epoch 2288/5000
10/10 - 0s - 8ms/step - loss: 2.1770e-07
Epoch 2289/5000
10/10 - 0s - 8ms/step - loss: 4.2069e-08
Epoch 2290/5000
10/10 - 0s - 9ms/step - loss: 2.4739e-08
Epoch 2291/5000
10/10 - 0s - 7ms/step - loss: 1.0310e-08
Epoch 2292/5000
10/10 - 0s - 8ms/step - loss: 1.7185e-09
Epoch 2293/5000
10/10 - 0s - 9ms/step - loss: 2.3058e-09
Epoch 2294/5000
10/10 - 0s - 8ms/step - loss: 2.4201e-09
Epoch 2295/5000
10/10 - 0s - 9ms/step - loss: 2.1424e-08
Epoch 2296/5000
10/10 - 0s - 10ms/step - loss: 1.7693e-07
Epoch 2297/5000
10/10 - 0s - 9ms/step - loss: 1.3997e-07
Epoch 2298/5000
10/10 - 0s - 9ms/step - loss: 4.2822e-08
Epoch 2299/5000
10/10 - 0s - 8ms/step - loss: 1.3465e-08
Epoch 2300/5000
10/10 - 0s - 8ms/step - loss: 4.7006e-09
Epoch 2301/5000
10/10 - 0s - 10ms/step - loss: 2.5095e-09
Epoch 2302/5000
10/10 - 0s - 8ms/step - loss: 2.3861e-10
Epoch 2303/5000
10/10 - 0s - 9ms/step - loss: 4.5731e-09
Epoch 2304/5000
10/10 - 0s - 9ms/step - loss: 3.4063e-08
Epoch 2305/5000
10/10 - 0s - 8ms/step - loss: 2.0487e-07
Epoch 2306/5000
10/10 - 0s - 9ms/step - loss: 7.8201e-08
Epoch 2307/5000
10/10 - 0s - 9ms/step - loss: 4.5239e-08
Epoch 2308/5000
10/10 - 0s - 9ms/step - loss: 2.0270e-08
Epoch 2309/5000
10/10 - 0s - 9ms/step - loss: 3.6823e-09
Epoch 2310/5000
10/10 - 0s - 9ms/step - loss: 5.6625e-09
Epoch 2311/5000
10/10 - 0s - 9ms/step - loss: 2.3191e-09
Epoch 2312/5000
10/10 - 0s - 8ms/step - loss: 8.4978e-10
Epoch 2313/5000
10/10 - 0s - 10ms/step - loss: 3.5104e-09
Epoch 2314/5000
10/10 - 0s - 9ms/step - loss: 5.1471e-08
Epoch 2315/5000
10/10 - 0s - 8ms/step - loss: 4.5279e-07
Epoch 2316/5000
10/10 - 0s - 9ms/step - loss: 9.8493e-08
Epoch 2317/5000
10/10 - 0s - 9ms/step - loss: 4.4000e-08
Epoch 2318/5000
10/10 - 0s - 10ms/step - loss: 1.9354e-08
Epoch 2319/5000
10/10 - 0s - 19ms/step - loss: 4.9688e-09
Epoch 2320/5000
10/10 - 0s - 18ms/step - loss: 2.7180e-09
Epoch 2321/5000
10/10 - 0s - 8ms/step - loss: 9.0368e-10
Epoch 2322/5000
10/10 - 0s - 9ms/step - loss: 4.5971e-10
Epoch 2323/5000
10/10 - 0s - 8ms/step - loss: 1.4883e-09
Epoch 2324/5000
10/10 - 0s - 8ms/step - loss: 5.3582e-10
Epoch 2325/5000
10/10 - 0s - 9ms/step - loss: 2.9238e-09
Epoch 2326/5000
10/10 - 0s - 9ms/step - loss: 6.7052e-10
Epoch 2327/5000
10/10 - 0s - 9ms/step - loss: 1.0093e-08
Epoch 2328/5000
10/10 - 0s - 9ms/step - loss: 9.4954e-08
Epoch 2329/5000
10/10 - 0s - 8ms/step - loss: 2.0029e-07
Epoch 2330/5000
10/10 - 0s - 9ms/step - loss: 3.6497e-08
Epoch 2331/5000
10/10 - 0s - 9ms/step - loss: 8.3022e-09
Epoch 2332/5000
10/10 - 0s - 9ms/step - loss: 3.5389e-09
Epoch 2333/5000
10/10 - 0s - 18ms/step - loss: 1.2146e-09
Epoch 2334/5000
10/10 - 0s - 9ms/step - loss: 5.3405e-10
Epoch 2335/5000
10/10 - 0s - 8ms/step - loss: 4.5266e-09
Epoch 2336/5000
10/10 - 0s - 8ms/step - loss: 2.3355e-08
Epoch 2337/5000
10/10 - 0s - 10ms/step - loss: 2.3578e-07
Epoch 2338/5000
10/10 - 0s - 9ms/step - loss: 1.5657e-07
Epoch 2339/5000
10/10 - 0s - 9ms/step - loss: 5.3920e-08
Epoch 2340/5000
10/10 - 0s - 10ms/step - loss: 2.1634e-08
Epoch 2341/5000
10/10 - 0s - 8ms/step - loss: 7.1789e-09
Epoch 2342/5000
10/10 - 0s - 8ms/step - loss: 3.0393e-09
Epoch 2343/5000
10/10 - 0s - 8ms/step - loss: 1.9953e-09
Epoch 2344/5000
10/10 - 0s - 9ms/step - loss: 5.9841e-10
Epoch 2345/5000
10/10 - 0s - 9ms/step - loss: 1.4406e-10
Epoch 2346/5000
10/10 - 0s - 9ms/step - loss: 5.3913e-09
Epoch 2347/5000
10/10 - 0s - 10ms/step - loss: 8.3954e-08
Epoch 2348/5000
10/10 - 0s - 8ms/step - loss: 2.1624e-07
Epoch 2349/5000
10/10 - 0s - 9ms/step - loss: 4.4452e-08
Epoch 2350/5000
10/10 - 0s - 9ms/step - loss: 1.4814e-08
Epoch 2351/5000
10/10 - 0s - 9ms/step - loss: 8.6055e-09
Epoch 2352/5000
10/10 - 0s - 9ms/step - loss: 2.4651e-09
Epoch 2353/5000
10/10 - 0s - 8ms/step - loss: 7.2406e-10
Epoch 2354/5000
10/10 - 0s - 9ms/step - loss: 8.9537e-09
Epoch 2355/5000
10/10 - 0s - 9ms/step - loss: 2.0039e-08
Epoch 2356/5000
10/10 - 0s - 9ms/step - loss: 1.3315e-07
Epoch 2357/5000
10/10 - 0s - 18ms/step - loss: 1.4719e-07
Epoch 2358/5000
10/10 - 0s - 9ms/step - loss: 4.2775e-08
Epoch 2359/5000
10/10 - 0s - 9ms/step - loss: 9.3529e-09
Epoch 2360/5000
10/10 - 0s - 16ms/step - loss: 1.0034e-08
Epoch 2361/5000
10/10 - 0s - 16ms/step - loss: 6.4881e-10
Epoch 2362/5000
10/10 - 0s - 7ms/step - loss: 4.4821e-10
Epoch 2363/5000
10/10 - 0s - 18ms/step - loss: 1.1435e-08
Epoch 2364/5000
10/10 - 0s - 10ms/step - loss: 1.2260e-07
Epoch 2365/5000
10/10 - 0s - 9ms/step - loss: 1.9147e-07
Epoch 2366/5000
10/10 - 0s - 8ms/step - loss: 4.5826e-08
Epoch 2367/5000
10/10 - 0s - 9ms/step - loss: 2.0499e-08
Epoch 2368/5000
10/10 - 0s - 8ms/step - loss: 4.8559e-09
Epoch 2369/5000
10/10 - 0s - 19ms/step - loss: 3.6519e-09
Epoch 2370/5000
10/10 - 0s - 9ms/step - loss: 9.6529e-10
Epoch 2371/5000
10/10 - 0s - 10ms/step - loss: 4.0409e-10
Epoch 2372/5000
10/10 - 0s - 9ms/step - loss: 2.1155e-09
Epoch 2373/5000
10/10 - 0s - 9ms/step - loss: 1.9446e-08
Epoch 2374/5000
10/10 - 0s - 9ms/step - loss: 2.7230e-07
Epoch 2375/5000
10/10 - 0s - 9ms/step - loss: 1.8731e-07
Epoch 2376/5000
10/10 - 0s - 8ms/step - loss: 6.3127e-08
Epoch 2377/5000
10/10 - 0s - 10ms/step - loss: 2.3187e-08
Epoch 2378/5000
10/10 - 0s - 18ms/step - loss: 9.2097e-09
Epoch 2379/5000
10/10 - 0s - 9ms/step - loss: 2.9759e-09
Epoch 2380/5000
10/10 - 0s - 9ms/step - loss: 8.2077e-10
Epoch 2381/5000
10/10 - 0s - 8ms/step - loss: 1.0965e-09
Epoch 2382/5000
10/10 - 0s - 8ms/step - loss: 4.1061e-10
Epoch 2383/5000
10/10 - 0s - 17ms/step - loss: 3.6446e-09
Epoch 2384/5000
10/10 - 0s - 10ms/step - loss: 1.3407e-08
Epoch 2385/5000
10/10 - 0s - 9ms/step - loss: 1.1986e-08
Epoch 2386/5000
10/10 - 0s - 8ms/step - loss: 5.0032e-08
Epoch 2387/5000
10/10 - 0s - 9ms/step - loss: 2.3126e-07
Epoch 2388/5000
10/10 - 0s - 7ms/step - loss: 5.0619e-08
Epoch 2389/5000
10/10 - 0s - 8ms/step - loss: 3.2080e-08
Epoch 2390/5000
10/10 - 0s - 9ms/step - loss: 1.8255e-08
Epoch 2391/5000
10/10 - 0s - 10ms/step - loss: 7.5075e-09
Epoch 2392/5000
10/10 - 0s - 9ms/step - loss: 1.3425e-09
Epoch 2393/5000
10/10 - 0s - 9ms/step - loss: 3.4202e-10
Epoch 2394/5000
10/10 - 0s - 8ms/step - loss: 5.2538e-09
Epoch 2395/5000
10/10 - 0s - 9ms/step - loss: 2.7470e-08
Epoch 2396/5000
10/10 - 0s - 8ms/step - loss: 2.3797e-07
Epoch 2397/5000
10/10 - 0s - 9ms/step - loss: 1.2372e-07
Epoch 2398/5000
10/10 - 0s - 9ms/step - loss: 4.5415e-08
Epoch 2399/5000
10/10 - 0s - 8ms/step - loss: 2.0830e-08
Epoch 2400/5000
10/10 - 0s - 8ms/step - loss: 7.4923e-09
Epoch 2401/5000
10/10 - 0s - 9ms/step - loss: 4.4695e-09
Epoch 2402/5000
10/10 - 0s - 9ms/step - loss: 1.4752e-09
Epoch 2403/5000
10/10 - 0s - 9ms/step - loss: 2.1886e-09
Epoch 2404/5000
10/10 - 0s - 8ms/step - loss: 1.0878e-09
Epoch 2405/5000
10/10 - 0s - 8ms/step - loss: 7.8163e-09
Epoch 2406/5000
10/10 - 0s - 7ms/step - loss: 5.5645e-08
Epoch 2407/5000
10/10 - 0s - 8ms/step - loss: 3.1608e-07
Epoch 2408/5000
10/10 - 0s - 8ms/step - loss: 7.6538e-08
Epoch 2409/5000
10/10 - 0s - 8ms/step - loss: 2.8112e-08
Epoch 2410/5000
10/10 - 0s - 8ms/step - loss: 8.5599e-09
Epoch 2411/5000
10/10 - 0s - 9ms/step - loss: 4.2276e-09
Epoch 2412/5000
10/10 - 0s - 9ms/step - loss: 2.7245e-09
Epoch 2413/5000
10/10 - 0s - 9ms/step - loss: 2.4279e-09
Epoch 2414/5000
10/10 - 0s - 9ms/step - loss: 6.0583e-09
Epoch 2415/5000
10/10 - 0s - 10ms/step - loss: 3.5864e-09
Epoch 2416/5000
10/10 - 0s - 10ms/step - loss: 1.6621e-09
Epoch 2417/5000
10/10 - 0s - 8ms/step - loss: 2.0009e-08
Epoch 2418/5000
10/10 - 0s - 10ms/step - loss: 2.6552e-07
Epoch 2419/5000
10/10 - 0s - 9ms/step - loss: 1.2246e-07
Epoch 2420/5000
10/10 - 0s - 9ms/step - loss: 4.2463e-08
Epoch 2421/5000
10/10 - 0s - 8ms/step - loss: 1.7673e-08
Epoch 2422/5000
10/10 - 0s - 10ms/step - loss: 4.6490e-09
Epoch 2423/5000
10/10 - 0s - 9ms/step - loss: 6.1964e-10
Epoch 2424/5000
10/10 - 0s - 8ms/step - loss: 1.9046e-10
Epoch 2425/5000
10/10 - 0s - 10ms/step - loss: 1.0904e-09
Epoch 2426/5000
10/10 - 0s - 18ms/step - loss: 2.5529e-11
Epoch 2427/5000
10/10 - 0s - 10ms/step - loss: 2.4918e-09
Epoch 2428/5000
10/10 - 0s - 9ms/step - loss: 4.7360e-08
Epoch 2429/5000
10/10 - 0s - 9ms/step - loss: 3.3352e-07
Epoch 2430/5000
10/10 - 0s - 10ms/step - loss: 7.6521e-08
Epoch 2431/5000
10/10 - 0s - 10ms/step - loss: 3.0342e-08
Epoch 2432/5000
10/10 - 0s - 9ms/step - loss: 1.4807e-08
Epoch 2433/5000
10/10 - 0s - 9ms/step - loss: 4.0503e-09
Epoch 2434/5000
10/10 - 0s - 9ms/step - loss: 7.7159e-10
Epoch 2435/5000
10/10 - 0s - 8ms/step - loss: 2.0742e-10
Epoch 2436/5000
10/10 - 0s - 7ms/step - loss: 1.5655e-09
Epoch 2437/5000
10/10 - 0s - 8ms/step - loss: 8.3061e-09
Epoch 2438/5000
10/10 - 0s - 10ms/step - loss: 1.8004e-08
Epoch 2439/5000
10/10 - 0s - 9ms/step - loss: 3.5269e-08
Epoch 2440/5000
10/10 - 0s - 8ms/step - loss: 1.6806e-07
Epoch 2441/5000
10/10 - 0s - 8ms/step - loss: 5.4506e-08
Epoch 2442/5000
10/10 - 0s - 10ms/step - loss: 2.8807e-08
Epoch 2443/5000
10/10 - 0s - 9ms/step - loss: 4.5704e-09
Epoch 2444/5000
10/10 - 0s - 9ms/step - loss: 2.6875e-09
Epoch 2445/5000
10/10 - 0s - 9ms/step - loss: 8.0054e-11
Epoch 2446/5000
10/10 - 0s - 9ms/step - loss: 1.6896e-09
Epoch 2447/5000
10/10 - 0s - 8ms/step - loss: 4.4925e-08
Epoch 2448/5000
10/10 - 0s - 8ms/step - loss: 4.2321e-07
Epoch 2449/5000
10/10 - 0s - 10ms/step - loss: 1.0200e-07
Epoch 2450/5000
10/10 - 0s - 9ms/step - loss: 3.5764e-08
Epoch 2451/5000
10/10 - 0s - 10ms/step - loss: 1.6214e-08
Epoch 2452/5000
10/10 - 0s - 16ms/step - loss: 6.7013e-09
Epoch 2453/5000
10/10 - 0s - 8ms/step - loss: 1.8583e-09
Epoch 2454/5000
10/10 - 0s - 8ms/step - loss: 8.8990e-10
Epoch 2455/5000
10/10 - 0s - 9ms/step - loss: 3.7984e-10
Epoch 2456/5000
10/10 - 0s - 8ms/step - loss: 7.3257e-10
Epoch 2457/5000
10/10 - 0s - 10ms/step - loss: 2.7627e-10
Epoch 2458/5000
10/10 - 0s - 10ms/step - loss: 2.3305e-09
Epoch 2459/5000
10/10 - 0s - 8ms/step - loss: 7.3797e-09
Epoch 2460/5000
10/10 - 0s - 9ms/step - loss: 3.5759e-08
Epoch 2461/5000
10/10 - 0s - 9ms/step - loss: 1.3207e-07
Epoch 2462/5000
10/10 - 0s - 9ms/step - loss: 9.0903e-08
Epoch 2463/5000
10/10 - 0s - 9ms/step - loss: 2.1298e-08
Epoch 2464/5000
10/10 - 0s - 9ms/step - loss: 5.0489e-09
Epoch 2465/5000
10/10 - 0s - 9ms/step - loss: 1.9035e-08
Epoch 2466/5000
10/10 - 0s - 9ms/step - loss: 6.1805e-09
Epoch 2467/5000
10/10 - 0s - 7ms/step - loss: 8.6849e-09
Epoch 2468/5000
10/10 - 0s - 9ms/step - loss: 5.3650e-08
Epoch 2469/5000
10/10 - 0s - 9ms/step - loss: 2.7229e-07
Epoch 2470/5000
10/10 - 0s - 10ms/step - loss: 6.7694e-08
Epoch 2471/5000
10/10 - 0s - 9ms/step - loss: 2.8070e-08
Epoch 2472/5000
10/10 - 0s - 10ms/step - loss: 9.4897e-09
Epoch 2473/5000
10/10 - 0s - 9ms/step - loss: 5.4443e-09
Epoch 2474/5000
10/10 - 0s - 8ms/step - loss: 2.8825e-09
Epoch 2475/5000
10/10 - 0s - 10ms/step - loss: 5.5185e-10
Epoch 2476/5000
10/10 - 0s - 8ms/step - loss: 2.6856e-10
Epoch 2477/5000
10/10 - 0s - 9ms/step - loss: 3.4854e-10
Epoch 2478/5000
10/10 - 0s - 9ms/step - loss: 1.6593e-08
Epoch 2479/5000
10/10 - 0s - 9ms/step - loss: 2.6690e-07
Epoch 2480/5000
10/10 - 0s - 9ms/step - loss: 1.8351e-07
Epoch 2481/5000
10/10 - 0s - 9ms/step - loss: 6.3151e-08
Epoch 2482/5000
10/10 - 0s - 8ms/step - loss: 2.1915e-08
Epoch 2483/5000
10/10 - 0s - 9ms/step - loss: 6.4273e-09
Epoch 2484/5000
10/10 - 0s - 9ms/step - loss: 2.9832e-09
Epoch 2485/5000
10/10 - 0s - 9ms/step - loss: 1.5850e-09
Epoch 2486/5000
10/10 - 0s - 9ms/step - loss: 1.6592e-09
Epoch 2487/5000
10/10 - 0s - 8ms/step - loss: 4.7670e-10
Epoch 2488/5000
10/10 - 0s - 15ms/step - loss: 2.5653e-09
Epoch 2489/5000
10/10 - 0s - 12ms/step - loss: 4.8384e-09
Epoch 2490/5000
10/10 - 0s - 10ms/step - loss: 1.4622e-08
Epoch 2491/5000
10/10 - 0s - 9ms/step - loss: 8.9496e-08
Epoch 2492/5000
10/10 - 0s - 7ms/step - loss: 2.2061e-07
Epoch 2493/5000
10/10 - 0s - 8ms/step - loss: 4.2740e-08
Epoch 2494/5000
10/10 - 0s - 10ms/step - loss: 1.7643e-08
Epoch 2495/5000
10/10 - 0s - 9ms/step - loss: 9.6298e-09
Epoch 2496/5000
10/10 - 0s - 9ms/step - loss: 1.0901e-08
Epoch 2497/5000
10/10 - 0s - 10ms/step - loss: 5.1102e-09
Epoch 2498/5000
10/10 - 0s - 9ms/step - loss: 2.2758e-08
Epoch 2499/5000
10/10 - 0s - 9ms/step - loss: 2.4482e-08
Epoch 2500/5000
10/10 - 0s - 9ms/step - loss: 2.3200e-08
Epoch 2501/5000
10/10 - 0s - 9ms/step - loss: 5.5967e-08
Epoch 2502/5000
10/10 - 0s - 9ms/step - loss: 1.6877e-07
Epoch 2503/5000
10/10 - 0s - 9ms/step - loss: 3.2011e-08
Epoch 2504/5000
10/10 - 0s - 8ms/step - loss: 2.8836e-08
Epoch 2505/5000
10/10 - 0s - 9ms/step - loss: 1.4559e-09
Epoch 2506/5000
10/10 - 0s - 8ms/step - loss: 3.7366e-09
Epoch 2507/5000
10/10 - 0s - 9ms/step - loss: 1.0425e-08
Epoch 2508/5000
10/10 - 0s - 8ms/step - loss: 6.7917e-08
Epoch 2509/5000
10/10 - 0s - 10ms/step - loss: 1.6846e-07
Epoch 2510/5000
10/10 - 0s - 9ms/step - loss: 2.4694e-08
Epoch 2511/5000
10/10 - 0s - 8ms/step - loss: 2.4742e-08
Epoch 2512/5000
10/10 - 0s - 9ms/step - loss: 8.6113e-09
Epoch 2513/5000
10/10 - 0s - 9ms/step - loss: 6.4880e-09
Epoch 2514/5000
10/10 - 0s - 10ms/step - loss: 1.1198e-09
Epoch 2515/5000
10/10 - 0s - 10ms/step - loss: 2.9502e-09
Epoch 2516/5000
10/10 - 0s - 8ms/step - loss: 3.7564e-08
Epoch 2517/5000
10/10 - 0s - 10ms/step - loss: 4.4581e-07
Epoch 2518/5000
10/10 - 0s - 8ms/step - loss: 1.1315e-07
Epoch 2519/5000
10/10 - 0s - 9ms/step - loss: 4.4048e-08
Epoch 2520/5000
10/10 - 0s - 9ms/step - loss: 2.3389e-08
Epoch 2521/5000
10/10 - 0s - 9ms/step - loss: 9.2366e-09
Epoch 2522/5000
10/10 - 0s - 10ms/step - loss: 3.2777e-09
Epoch 2523/5000
10/10 - 0s - 9ms/step - loss: 1.8839e-09
Epoch 2524/5000
10/10 - 0s - 9ms/step - loss: 5.1919e-10
Epoch 2525/5000
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Epoch 2526/5000
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Epoch 2527/5000
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Epoch 2528/5000
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Epoch 2529/5000
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Epoch 2530/5000
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Epoch 2531/5000
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Epoch 2532/5000
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Epoch 2533/5000
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Epoch 2534/5000
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Epoch 2535/5000
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Epoch 2536/5000
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Epoch 2537/5000
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Epoch 2538/5000
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Epoch 2539/5000
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Epoch 2540/5000
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Epoch 2541/5000
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Epoch 2542/5000
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Epoch 2543/5000
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Epoch 2544/5000
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Epoch 2545/5000
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Epoch 2546/5000
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Epoch 2547/5000
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Epoch 2548/5000
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Epoch 2549/5000
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Epoch 2550/5000
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Epoch 2551/5000
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Epoch 2552/5000
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Epoch 2553/5000
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Epoch 2554/5000
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Epoch 2555/5000
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Epoch 2556/5000
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Epoch 2557/5000
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Epoch 2558/5000
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Epoch 2559/5000
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Epoch 2560/5000
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Epoch 2561/5000
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Epoch 2562/5000
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Epoch 2563/5000
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Epoch 2564/5000
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Epoch 2565/5000
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Epoch 2566/5000
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Epoch 2567/5000
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Epoch 2568/5000
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Epoch 2569/5000
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Epoch 2570/5000
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Epoch 2571/5000
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Epoch 2572/5000
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Epoch 2573/5000
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Epoch 2574/5000
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Epoch 2575/5000
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Epoch 2576/5000
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Epoch 2577/5000
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Epoch 2578/5000
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Epoch 2579/5000
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Epoch 2580/5000
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Epoch 2581/5000
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Epoch 2582/5000
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Epoch 2583/5000
10/10 - 0s - 8ms/step - loss: 7.0972e-08
Epoch 2584/5000
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Epoch 2585/5000
10/10 - 0s - 18ms/step - loss: 7.9337e-09
Epoch 2586/5000
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Epoch 2587/5000
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Epoch 2588/5000
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Epoch 2589/5000
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Epoch 2590/5000
10/10 - 0s - 9ms/step - loss: 3.4761e-09
Epoch 2591/5000
10/10 - 0s - 9ms/step - loss: 4.6508e-08
Epoch 2592/5000
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Epoch 2593/5000
10/10 - 0s - 9ms/step - loss: 5.2819e-08
Epoch 2594/5000
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Epoch 2595/5000
10/10 - 0s - 15ms/step - loss: 8.6333e-09
Epoch 2596/5000
10/10 - 0s - 14ms/step - loss: 6.5006e-09
Epoch 2597/5000
10/10 - 0s - 8ms/step - loss: 1.3216e-09
Epoch 2598/5000
10/10 - 0s - 8ms/step - loss: 5.7708e-10
Epoch 2599/5000
10/10 - 0s - 8ms/step - loss: 3.1910e-09
Epoch 2600/5000
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Epoch 2601/5000
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Epoch 2602/5000
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Epoch 2603/5000
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Epoch 2604/5000
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Epoch 2605/5000
10/10 - 0s - 9ms/step - loss: 3.8906e-09
Epoch 2606/5000
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Epoch 2607/5000
10/10 - 0s - 9ms/step - loss: 5.1032e-10
Epoch 2608/5000
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Epoch 2609/5000
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Epoch 2610/5000
10/10 - 0s - 10ms/step - loss: 2.7492e-10
Epoch 2611/5000
10/10 - 0s - 16ms/step - loss: 2.2995e-09
Epoch 2612/5000
10/10 - 0s - 9ms/step - loss: 2.5756e-08
Epoch 2613/5000
10/10 - 0s - 9ms/step - loss: 4.7628e-07
Epoch 2614/5000
10/10 - 0s - 7ms/step - loss: 1.5274e-07
Epoch 2615/5000
10/10 - 0s - 8ms/step - loss: 5.1362e-08
Epoch 2616/5000
10/10 - 0s - 9ms/step - loss: 2.8370e-08
Epoch 2617/5000
10/10 - 0s - 9ms/step - loss: 8.0448e-09
Epoch 2618/5000
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Epoch 2619/5000
10/10 - 0s - 10ms/step - loss: 1.7193e-09
Epoch 2620/5000
10/10 - 0s - 9ms/step - loss: 6.1836e-10
Epoch 2621/5000
10/10 - 0s - 8ms/step - loss: 5.3260e-10
Epoch 2622/5000
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Epoch 2623/5000
10/10 - 0s - 8ms/step - loss: 8.3956e-11
Epoch 2624/5000
10/10 - 0s - 8ms/step - loss: 8.4970e-11
Epoch 2625/5000
10/10 - 0s - 8ms/step - loss: 6.7269e-11
Epoch 2626/5000
10/10 - 0s - 8ms/step - loss: 1.4115e-09
Epoch 2627/5000
10/10 - 0s - 9ms/step - loss: 1.1754e-08
Epoch 2628/5000
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Epoch 2629/5000
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Epoch 2630/5000
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Epoch 2631/5000
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Epoch 2632/5000
10/10 - 0s - 17ms/step - loss: 8.1834e-09
Epoch 2633/5000
10/10 - 0s - 9ms/step - loss: 1.9078e-09
Epoch 2634/5000
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Epoch 2635/5000
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Epoch 2636/5000
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Epoch 2637/5000
10/10 - 0s - 10ms/step - loss: 1.5160e-08
Epoch 2638/5000
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Epoch 2639/5000
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Epoch 2640/5000
10/10 - 0s - 8ms/step - loss: 5.6709e-08
Epoch 2641/5000
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Epoch 2642/5000
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Epoch 2643/5000
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Epoch 2644/5000
10/10 - 0s - 10ms/step - loss: 6.8347e-10
Epoch 2645/5000
10/10 - 0s - 8ms/step - loss: 9.3003e-10
Epoch 2646/5000
10/10 - 0s - 9ms/step - loss: 2.3176e-10
Epoch 2647/5000
10/10 - 0s - 8ms/step - loss: 1.1611e-09
Epoch 2648/5000
10/10 - 0s - 9ms/step - loss: 2.0708e-08
Epoch 2649/5000
10/10 - 0s - 9ms/step - loss: 4.6839e-07
Epoch 2650/5000
10/10 - 0s - 10ms/step - loss: 1.8547e-07
Epoch 2651/5000
10/10 - 0s - 9ms/step - loss: 6.1043e-08
Epoch 2652/5000
10/10 - 0s - 8ms/step - loss: 3.2320e-08
Epoch 2653/5000
10/10 - 0s - 9ms/step - loss: 7.8667e-09
Epoch 2654/5000
10/10 - 0s - 8ms/step - loss: 4.6744e-09
Epoch 2655/5000
10/10 - 0s - 9ms/step - loss: 2.0103e-09
Epoch 2656/5000
10/10 - 0s - 8ms/step - loss: 3.7744e-10
Epoch 2657/5000
10/10 - 0s - 10ms/step - loss: 8.1736e-12
Epoch 2658/5000
10/10 - 0s - 9ms/step - loss: 1.2900e-10
Epoch 2659/5000
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Epoch 2660/5000
10/10 - 0s - 11ms/step - loss: 6.0752e-10
Epoch 2661/5000
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Epoch 2662/5000
10/10 - 0s - 10ms/step - loss: 2.7220e-09
Epoch 2663/5000
10/10 - 0s - 9ms/step - loss: 1.6914e-09
Epoch 2664/5000
10/10 - 0s - 7ms/step - loss: 8.9160e-11
Epoch 2665/5000
10/10 - 0s - 8ms/step - loss: 6.7332e-09
Epoch 2666/5000
10/10 - 0s - 8ms/step - loss: 1.4057e-07
Epoch 2667/5000
10/10 - 0s - 9ms/step - loss: 3.4480e-07
Epoch 2668/5000
10/10 - 0s - 8ms/step - loss: 1.1191e-07
Epoch 2669/5000
10/10 - 0s - 9ms/step - loss: 3.8883e-08
Epoch 2670/5000
10/10 - 0s - 8ms/step - loss: 1.1361e-08
Epoch 2671/5000
10/10 - 0s - 9ms/step - loss: 2.5864e-09
Epoch 2672/5000
10/10 - 0s - 9ms/step - loss: 1.9318e-09
Epoch 2673/5000
10/10 - 0s - 9ms/step - loss: 7.3642e-10
Epoch 2674/5000
10/10 - 0s - 10ms/step - loss: 9.5149e-10
Epoch 2675/5000
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Epoch 2676/5000
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Epoch 2677/5000
10/10 - 0s - 7ms/step - loss: 5.8297e-10
Epoch 2678/5000
10/10 - 0s - 9ms/step - loss: 2.3578e-09
Epoch 2679/5000
10/10 - 0s - 8ms/step - loss: 1.0218e-09
Epoch 2680/5000
10/10 - 0s - 9ms/step - loss: 7.4430e-09
Epoch 2681/5000
10/10 - 0s - 9ms/step - loss: 1.9277e-07
Epoch 2682/5000
10/10 - 0s - 8ms/step - loss: 2.7501e-07
Epoch 2683/5000
10/10 - 0s - 9ms/step - loss: 8.1284e-08
Epoch 2684/5000
10/10 - 0s - 8ms/step - loss: 2.8711e-08
Epoch 2685/5000
10/10 - 0s - 9ms/step - loss: 7.7775e-09
Epoch 2686/5000
10/10 - 0s - 8ms/step - loss: 4.2119e-09
Epoch 2687/5000
10/10 - 0s - 9ms/step - loss: 1.7224e-09
Epoch 2688/5000
10/10 - 0s - 8ms/step - loss: 2.2104e-10
Epoch 2689/5000
10/10 - 0s - 10ms/step - loss: 6.7138e-10
Epoch 2690/5000
10/10 - 0s - 8ms/step - loss: 1.1415e-09
Epoch 2691/5000
10/10 - 0s - 8ms/step - loss: 1.1790e-10
Epoch 2692/5000
10/10 - 0s - 9ms/step - loss: 8.4854e-10
Epoch 2693/5000
10/10 - 0s - 9ms/step - loss: 3.7309e-10
Epoch 2694/5000
10/10 - 0s - 10ms/step - loss: 2.1600e-08
Epoch 2695/5000
10/10 - 0s - 8ms/step - loss: 3.4910e-07
Epoch 2696/5000
10/10 - 0s - 8ms/step - loss: 1.6001e-07
Epoch 2697/5000
10/10 - 0s - 9ms/step - loss: 4.0317e-08
Epoch 2698/5000
10/10 - 0s - 8ms/step - loss: 1.2234e-08
Epoch 2699/5000
10/10 - 0s - 9ms/step - loss: 6.7642e-09
Epoch 2700/5000
10/10 - 0s - 8ms/step - loss: 3.6682e-09
Epoch 2701/5000
10/10 - 0s - 8ms/step - loss: 2.9307e-09
Epoch 2702/5000
10/10 - 0s - 8ms/step - loss: 1.7955e-09
Epoch 2703/5000
10/10 - 0s - 9ms/step - loss: 7.1299e-10
Epoch 2704/5000
10/10 - 0s - 9ms/step - loss: 1.6875e-09
Epoch 2705/5000
10/10 - 0s - 9ms/step - loss: 5.3001e-10
Epoch 2706/5000
10/10 - 0s - 9ms/step - loss: 3.9451e-10
Epoch 2707/5000
10/10 - 0s - 10ms/step - loss: 7.2385e-10
Epoch 2708/5000
10/10 - 0s - 8ms/step - loss: 1.8963e-08
Epoch 2709/5000
10/10 - 0s - 9ms/step - loss: 3.7633e-07
Epoch 2710/5000
10/10 - 0s - 8ms/step - loss: 2.3375e-07
Epoch 2711/5000
10/10 - 0s - 8ms/step - loss: 5.7709e-08
Epoch 2712/5000
10/10 - 0s - 8ms/step - loss: 2.6656e-08
Epoch 2713/5000
10/10 - 0s - 9ms/step - loss: 1.1775e-08
Epoch 2714/5000
10/10 - 0s - 7ms/step - loss: 5.1037e-09
Epoch 2715/5000
10/10 - 0s - 10ms/step - loss: 2.6614e-09
Epoch 2716/5000
10/10 - 0s - 9ms/step - loss: 2.1408e-09
Epoch 2717/5000
10/10 - 0s - 10ms/step - loss: 8.9660e-10
Epoch 2718/5000
10/10 - 0s - 9ms/step - loss: 3.7697e-10
Epoch 2719/5000
10/10 - 0s - 9ms/step - loss: 1.3889e-10
Epoch 2720/5000
10/10 - 0s - 9ms/step - loss: 4.6408e-10
Epoch 2721/5000
10/10 - 0s - 11ms/step - loss: 9.7758e-10
Epoch 2722/5000
10/10 - 0s - 8ms/step - loss: 3.4197e-09
Epoch 2723/5000
10/10 - 0s - 8ms/step - loss: 7.5901e-09
Epoch 2724/5000
10/10 - 0s - 10ms/step - loss: 3.1671e-08
Epoch 2725/5000
10/10 - 0s - 10ms/step - loss: 2.2943e-07
Epoch 2726/5000
10/10 - 0s - 9ms/step - loss: 1.0594e-07
Epoch 2727/5000
10/10 - 0s - 14ms/step - loss: 3.6028e-08
Epoch 2728/5000
10/10 - 0s - 9ms/step - loss: 1.3853e-08
Epoch 2729/5000
10/10 - 0s - 10ms/step - loss: 5.1322e-09
Epoch 2730/5000
10/10 - 0s - 10ms/step - loss: 4.5974e-10
Epoch 2731/5000
10/10 - 0s - 8ms/step - loss: 2.4539e-10
Epoch 2732/5000
10/10 - 0s - 9ms/step - loss: 3.2410e-09
Epoch 2733/5000
10/10 - 0s - 8ms/step - loss: 2.3229e-08
Epoch 2734/5000
10/10 - 0s - 9ms/step - loss: 1.3277e-07
Epoch 2735/5000
10/10 - 0s - 9ms/step - loss: 8.2736e-08
Epoch 2736/5000
10/10 - 0s - 10ms/step - loss: 2.6292e-08
Epoch 2737/5000
10/10 - 0s - 8ms/step - loss: 4.7589e-09
Epoch 2738/5000
10/10 - 0s - 10ms/step - loss: 7.9638e-09
Epoch 2739/5000
10/10 - 0s - 9ms/step - loss: 4.4635e-09
Epoch 2740/5000
10/10 - 0s - 20ms/step - loss: 8.3684e-09
Epoch 2741/5000
10/10 - 0s - 10ms/step - loss: 8.9132e-08
Epoch 2742/5000
10/10 - 0s - 9ms/step - loss: 2.8006e-07
Epoch 2743/5000
10/10 - 0s - 8ms/step - loss: 5.7570e-08
Epoch 2744/5000
10/10 - 0s - 8ms/step - loss: 2.3993e-08
Epoch 2745/5000
10/10 - 0s - 9ms/step - loss: 8.9572e-09
Epoch 2746/5000
10/10 - 0s - 8ms/step - loss: 2.9982e-09
Epoch 2747/5000
10/10 - 0s - 9ms/step - loss: 3.0511e-10
Epoch 2748/5000
10/10 - 0s - 8ms/step - loss: 7.7698e-11
Epoch 2749/5000
10/10 - 0s - 18ms/step - loss: 1.3949e-09
Epoch 2750/5000
10/10 - 0s - 18ms/step - loss: 2.3319e-09
Epoch 2751/5000
10/10 - 0s - 11ms/step - loss: 1.4936e-08
Epoch 2752/5000
10/10 - 0s - 9ms/step - loss: 1.4084e-07
Epoch 2753/5000
10/10 - 0s - 8ms/step - loss: 1.6753e-07
Epoch 2754/5000
10/10 - 0s - 10ms/step - loss: 4.6896e-08
Epoch 2755/5000
10/10 - 0s - 10ms/step - loss: 2.0067e-08
Epoch 2756/5000
10/10 - 0s - 7ms/step - loss: 8.3031e-09
Epoch 2757/5000
10/10 - 0s - 9ms/step - loss: 1.6309e-09
Epoch 2758/5000
10/10 - 0s - 8ms/step - loss: 2.6048e-09
Epoch 2759/5000
10/10 - 0s - 9ms/step - loss: 1.2898e-09
Epoch 2760/5000
10/10 - 0s - 9ms/step - loss: 7.9604e-09
Epoch 2761/5000
10/10 - 0s - 9ms/step - loss: 6.1305e-08
Epoch 2762/5000
10/10 - 0s - 8ms/step - loss: 2.0506e-07
Epoch 2763/5000
10/10 - 0s - 8ms/step - loss: 4.2347e-08
Epoch 2764/5000
10/10 - 0s - 8ms/step - loss: 2.7284e-08
Epoch 2765/5000
10/10 - 0s - 10ms/step - loss: 1.8796e-08
Epoch 2766/5000
10/10 - 0s - 9ms/step - loss: 3.1667e-09
Epoch 2767/5000
10/10 - 0s - 9ms/step - loss: 3.0943e-09
Epoch 2768/5000
10/10 - 0s - 10ms/step - loss: 3.9944e-10
Epoch 2769/5000
10/10 - 0s - 8ms/step - loss: 1.3847e-10
Epoch 2770/5000
10/10 - 0s - 10ms/step - loss: 2.4633e-10
Epoch 2771/5000
10/10 - 0s - 9ms/step - loss: 5.2472e-09
Epoch 2772/5000
10/10 - 0s - 9ms/step - loss: 3.1319e-07
Epoch 2773/5000
10/10 - 0s - 10ms/step - loss: 4.8507e-07
Epoch 2774/5000
10/10 - 0s - 12ms/step - loss: 9.4875e-08
Epoch 2775/5000
10/10 - 0s - 19ms/step - loss: 4.7448e-08
Epoch 2776/5000
10/10 - 0s - 9ms/step - loss: 1.3304e-08
Epoch 2777/5000
10/10 - 0s - 8ms/step - loss: 3.9094e-09
Epoch 2778/5000
10/10 - 0s - 8ms/step - loss: 2.0230e-09
Epoch 2779/5000
10/10 - 0s - 8ms/step - loss: 6.8288e-10
Epoch 2780/5000
10/10 - 0s - 10ms/step - loss: 1.0192e-09
Epoch 2781/5000
10/10 - 0s - 9ms/step - loss: 2.1472e-10
Epoch 2782/5000
10/10 - 0s - 11ms/step - loss: 7.7153e-10
Epoch 2783/5000
10/10 - 0s - 10ms/step - loss: 2.8609e-10
Epoch 2784/5000
10/10 - 0s - 9ms/step - loss: 8.4447e-11
Epoch 2785/5000
10/10 - 0s - 10ms/step - loss: 1.4443e-10
Epoch 2786/5000
10/10 - 0s - 10ms/step - loss: 4.0349e-11
Epoch 2787/5000
10/10 - 0s - 8ms/step - loss: 1.1321e-10
Epoch 2788/5000
10/10 - 0s - 10ms/step - loss: 7.2919e-10
Epoch 2789/5000
10/10 - 0s - 10ms/step - loss: 2.1263e-09
Epoch 2790/5000
10/10 - 0s - 11ms/step - loss: 1.9476e-09
Epoch 2791/5000
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Epoch 2792/5000
10/10 - 0s - 9ms/step - loss: 2.3898e-07
Epoch 2793/5000
10/10 - 0s - 8ms/step - loss: 4.6644e-08
Epoch 2794/5000
10/10 - 0s - 9ms/step - loss: 1.9800e-08
Epoch 2795/5000
10/10 - 0s - 9ms/step - loss: 8.9669e-09
Epoch 2796/5000
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Epoch 2797/5000
10/10 - 0s - 9ms/step - loss: 1.1335e-09
Epoch 2798/5000
10/10 - 0s - 9ms/step - loss: 9.1060e-09
Epoch 2799/5000
10/10 - 0s - 9ms/step - loss: 1.1479e-08
Epoch 2800/5000
10/10 - 0s - 9ms/step - loss: 1.1915e-08
Epoch 2801/5000
10/10 - 0s - 9ms/step - loss: 1.3115e-07
Epoch 2802/5000
10/10 - 0s - 9ms/step - loss: 1.9762e-07
Epoch 2803/5000
10/10 - 0s - 9ms/step - loss: 6.9554e-08
Epoch 2804/5000
10/10 - 0s - 8ms/step - loss: 2.4201e-08
Epoch 2805/5000
10/10 - 0s - 8ms/step - loss: 1.5831e-08
Epoch 2806/5000
10/10 - 0s - 9ms/step - loss: 4.3561e-09
Epoch 2807/5000
10/10 - 0s - 8ms/step - loss: 2.0553e-09
Epoch 2808/5000
10/10 - 0s - 9ms/step - loss: 2.0514e-09
Epoch 2809/5000
10/10 - 0s - 8ms/step - loss: 1.0811e-10
Epoch 2810/5000
10/10 - 0s - 10ms/step - loss: 2.9246e-09
Epoch 2811/5000
10/10 - 0s - 9ms/step - loss: 2.6014e-08
Epoch 2812/5000
10/10 - 0s - 8ms/step - loss: 2.0789e-07
Epoch 2813/5000
10/10 - 0s - 8ms/step - loss: 1.2519e-07
Epoch 2814/5000
10/10 - 0s - 9ms/step - loss: 5.1382e-08
Epoch 2815/5000
10/10 - 0s - 8ms/step - loss: 1.6775e-08
Epoch 2816/5000
10/10 - 0s - 8ms/step - loss: 6.8437e-09
Epoch 2817/5000
10/10 - 0s - 9ms/step - loss: 3.1861e-09
Epoch 2818/5000
10/10 - 0s - 9ms/step - loss: 6.9521e-10
Epoch 2819/5000
10/10 - 0s - 9ms/step - loss: 4.6696e-11
Epoch 2820/5000
10/10 - 0s - 9ms/step - loss: 9.4447e-11
Epoch 2821/5000
10/10 - 0s - 9ms/step - loss: 3.8899e-10
Epoch 2822/5000
10/10 - 0s - 9ms/step - loss: 4.9645e-09
Epoch 2823/5000
10/10 - 0s - 8ms/step - loss: 1.8887e-07
Epoch 2824/5000
10/10 - 0s - 9ms/step - loss: 3.6434e-07
Epoch 2825/5000
10/10 - 0s - 10ms/step - loss: 1.1409e-07
Epoch 2826/5000
10/10 - 0s - 8ms/step - loss: 2.7003e-08
Epoch 2827/5000
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Epoch 2828/5000
10/10 - 0s - 9ms/step - loss: 8.2292e-09
Epoch 2829/5000
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Epoch 2830/5000
10/10 - 0s - 8ms/step - loss: 1.5363e-09
Epoch 2831/5000
10/10 - 0s - 9ms/step - loss: 1.0285e-09
Epoch 2832/5000
10/10 - 0s - 10ms/step - loss: 2.5235e-10
Epoch 2833/5000
10/10 - 0s - 9ms/step - loss: 9.2525e-10
Epoch 2834/5000
10/10 - 0s - 9ms/step - loss: 7.1992e-10
Epoch 2835/5000
10/10 - 0s - 9ms/step - loss: 5.9439e-11
Epoch 2836/5000
10/10 - 0s - 9ms/step - loss: 7.1991e-10
Epoch 2837/5000
10/10 - 0s - 9ms/step - loss: 7.6767e-09
Epoch 2838/5000
10/10 - 0s - 24ms/step - loss: 3.5674e-08
Epoch 2839/5000
10/10 - 0s - 9ms/step - loss: 2.1363e-07
Epoch 2840/5000
10/10 - 0s - 10ms/step - loss: 7.7760e-08
Epoch 2841/5000
10/10 - 0s - 8ms/step - loss: 2.6859e-08
Epoch 2842/5000
10/10 - 0s - 10ms/step - loss: 1.5139e-08
Epoch 2843/5000
10/10 - 0s - 9ms/step - loss: 2.3674e-09
Epoch 2844/5000
10/10 - 0s - 10ms/step - loss: 1.0411e-09
Epoch 2845/5000
10/10 - 0s - 10ms/step - loss: 1.5157e-09
Epoch 2846/5000
10/10 - 0s - 8ms/step - loss: 4.4145e-09
Epoch 2847/5000
10/10 - 0s - 9ms/step - loss: 2.3681e-08
Epoch 2848/5000
10/10 - 0s - 10ms/step - loss: 2.1401e-07
Epoch 2849/5000
10/10 - 0s - 8ms/step - loss: 1.2899e-07
Epoch 2850/5000
10/10 - 0s - 10ms/step - loss: 4.9876e-08
Epoch 2851/5000
10/10 - 0s - 9ms/step - loss: 1.8052e-08
Epoch 2852/5000
10/10 - 0s - 9ms/step - loss: 7.0765e-09
Epoch 2853/5000
10/10 - 0s - 9ms/step - loss: 2.5787e-09
Epoch 2854/5000
10/10 - 0s - 10ms/step - loss: 5.2491e-10
Epoch 2855/5000
10/10 - 0s - 10ms/step - loss: 2.3132e-10
Epoch 2856/5000
10/10 - 0s - 8ms/step - loss: 6.1221e-10
Epoch 2857/5000
10/10 - 0s - 9ms/step - loss: 3.1859e-09
Epoch 2858/5000
10/10 - 0s - 9ms/step - loss: 3.7545e-08
Epoch 2859/5000
10/10 - 0s - 8ms/step - loss: 3.3531e-07
Epoch 2860/5000
10/10 - 0s - 9ms/step - loss: 1.0451e-07
Epoch 2861/5000
10/10 - 0s - 9ms/step - loss: 3.6667e-08
Epoch 2862/5000
10/10 - 0s - 9ms/step - loss: 1.2091e-08
Epoch 2863/5000
10/10 - 0s - 9ms/step - loss: 6.9103e-09
Epoch 2864/5000
10/10 - 0s - 9ms/step - loss: 3.1318e-09
Epoch 2865/5000
10/10 - 0s - 8ms/step - loss: 1.8590e-09
Epoch 2866/5000
10/10 - 0s - 9ms/step - loss: 1.0527e-09
Epoch 2867/5000
10/10 - 0s - 10ms/step - loss: 2.9964e-09
Epoch 2868/5000
10/10 - 0s - 9ms/step - loss: 8.2473e-10
Epoch 2869/5000
10/10 - 0s - 8ms/step - loss: 2.6452e-09
Epoch 2870/5000
10/10 - 0s - 8ms/step - loss: 8.9846e-09
Epoch 2871/5000
10/10 - 0s - 9ms/step - loss: 1.3745e-07
Epoch 2872/5000
10/10 - 0s - 8ms/step - loss: 2.2753e-07
Epoch 2873/5000
10/10 - 0s - 9ms/step - loss: 6.2907e-08
Epoch 2874/5000
10/10 - 0s - 8ms/step - loss: 2.0711e-08
Epoch 2875/5000
10/10 - 0s - 10ms/step - loss: 8.8638e-09
Epoch 2876/5000
10/10 - 0s - 9ms/step - loss: 2.6055e-09
Epoch 2877/5000
10/10 - 0s - 7ms/step - loss: 6.1878e-10
Epoch 2878/5000
10/10 - 0s - 9ms/step - loss: 4.1982e-10
Epoch 2879/5000
10/10 - 0s - 9ms/step - loss: 1.3211e-09
Epoch 2880/5000
10/10 - 0s - 8ms/step - loss: 1.0605e-09
Epoch 2881/5000
10/10 - 0s - 8ms/step - loss: 7.1736e-10
Epoch 2882/5000
10/10 - 0s - 10ms/step - loss: 1.6010e-08
Epoch 2883/5000
10/10 - 0s - 8ms/step - loss: 3.3829e-07
Epoch 2884/5000
10/10 - 0s - 8ms/step - loss: 2.0541e-07
Epoch 2885/5000
10/10 - 0s - 9ms/step - loss: 5.4374e-08
Epoch 2886/5000
10/10 - 0s - 9ms/step - loss: 1.8262e-08
Epoch 2887/5000
10/10 - 0s - 8ms/step - loss: 1.2177e-08
Epoch 2888/5000
10/10 - 0s - 10ms/step - loss: 5.0100e-09
Epoch 2889/5000
10/10 - 0s - 7ms/step - loss: 1.2957e-09
Epoch 2890/5000
10/10 - 0s - 8ms/step - loss: 8.3249e-10
Epoch 2891/5000
10/10 - 0s - 10ms/step - loss: 6.8059e-10
Epoch 2892/5000
10/10 - 0s - 9ms/step - loss: 7.5372e-10
Epoch 2893/5000
10/10 - 0s - 9ms/step - loss: 2.6895e-10
Epoch 2894/5000
10/10 - 0s - 9ms/step - loss: 4.0813e-10
Epoch 2895/5000
10/10 - 0s - 7ms/step - loss: 2.5331e-10
Epoch 2896/5000
10/10 - 0s - 8ms/step - loss: 1.2341e-10
Epoch 2897/5000
10/10 - 0s - 9ms/step - loss: 7.9417e-09
Epoch 2898/5000
10/10 - 0s - 9ms/step - loss: 3.0260e-07
Epoch 2899/5000
10/10 - 0s - 8ms/step - loss: 2.6622e-07
Epoch 2900/5000
10/10 - 0s - 9ms/step - loss: 7.3075e-08
Epoch 2901/5000
10/10 - 0s - 9ms/step - loss: 1.9520e-08
Epoch 2902/5000
10/10 - 0s - 8ms/step - loss: 9.0504e-09
Epoch 2903/5000
10/10 - 0s - 10ms/step - loss: 2.5888e-09
Epoch 2904/5000
10/10 - 0s - 22ms/step - loss: 5.9591e-10
Epoch 2905/5000
10/10 - 0s - 10ms/step - loss: 5.6891e-10
Epoch 2906/5000
10/10 - 0s - 8ms/step - loss: 3.2506e-10
Epoch 2907/5000
10/10 - 0s - 8ms/step - loss: 5.0922e-10
Epoch 2908/5000
10/10 - 0s - 9ms/step - loss: 7.0282e-10
Epoch 2909/5000
10/10 - 0s - 10ms/step - loss: 6.8450e-10
Epoch 2910/5000
10/10 - 0s - 8ms/step - loss: 1.5361e-10
Epoch 2911/5000
10/10 - 0s - 8ms/step - loss: 2.3505e-09
Epoch 2912/5000
10/10 - 0s - 9ms/step - loss: 1.2414e-08
Epoch 2913/5000
10/10 - 0s - 8ms/step - loss: 1.3657e-07
Epoch 2914/5000
10/10 - 0s - 9ms/step - loss: 1.9166e-07
Epoch 2915/5000
10/10 - 0s - 9ms/step - loss: 6.1492e-08
Epoch 2916/5000
10/10 - 0s - 8ms/step - loss: 2.4041e-08
Epoch 2917/5000
10/10 - 0s - 9ms/step - loss: 8.9905e-09
Epoch 2918/5000
10/10 - 0s - 9ms/step - loss: 5.1344e-09
Epoch 2919/5000
10/10 - 0s - 9ms/step - loss: 3.3149e-09
Epoch 2920/5000
10/10 - 0s - 9ms/step - loss: 1.9623e-10
Epoch 2921/5000
10/10 - 0s - 10ms/step - loss: 9.8099e-10
Epoch 2922/5000
10/10 - 0s - 9ms/step - loss: 2.4411e-09
Epoch 2923/5000
10/10 - 0s - 9ms/step - loss: 2.9891e-08
Epoch 2924/5000
10/10 - 0s - 10ms/step - loss: 3.0156e-07
Epoch 2925/5000
10/10 - 0s - 8ms/step - loss: 9.5974e-08
Epoch 2926/5000
10/10 - 0s - 9ms/step - loss: 3.0242e-08
Epoch 2927/5000
10/10 - 0s - 9ms/step - loss: 1.1251e-08
Epoch 2928/5000
10/10 - 0s - 10ms/step - loss: 3.6729e-09
Epoch 2929/5000
10/10 - 0s - 9ms/step - loss: 1.4774e-09
Epoch 2930/5000
10/10 - 0s - 9ms/step - loss: 2.2363e-09
Epoch 2931/5000
10/10 - 0s - 7ms/step - loss: 1.7908e-10
Epoch 2932/5000
10/10 - 0s - 9ms/step - loss: 3.1951e-11
Epoch 2933/5000
10/10 - 0s - 9ms/step - loss: 5.8004e-10
Epoch 2934/5000
10/10 - 0s - 8ms/step - loss: 4.3600e-09
Epoch 2935/5000
10/10 - 0s - 8ms/step - loss: 9.3815e-08
Epoch 2936/5000
10/10 - 0s - 8ms/step - loss: 3.3763e-07
Epoch 2937/5000
10/10 - 0s - 9ms/step - loss: 9.6567e-08
Epoch 2938/5000
10/10 - 0s - 9ms/step - loss: 4.0056e-08
Epoch 2939/5000
10/10 - 0s - 7ms/step - loss: 1.3713e-08
Epoch 2940/5000
10/10 - 0s - 9ms/step - loss: 5.8436e-09
Epoch 2941/5000
10/10 - 0s - 9ms/step - loss: 2.6373e-09
Epoch 2942/5000
10/10 - 0s - 9ms/step - loss: 6.5729e-10
Epoch 2943/5000
10/10 - 0s - 8ms/step - loss: 1.6683e-10
Epoch 2944/5000
10/10 - 0s - 9ms/step - loss: 3.9093e-10
Epoch 2945/5000
10/10 - 0s - 9ms/step - loss: 1.9090e-10
Epoch 2946/5000
10/10 - 0s - 9ms/step - loss: 2.9697e-09
Epoch 2947/5000
10/10 - 0s - 8ms/step - loss: 1.2991e-08
Epoch 2948/5000
10/10 - 0s - 7ms/step - loss: 6.8686e-08
Epoch 2949/5000
10/10 - 0s - 9ms/step - loss: 1.6619e-07
Epoch 2950/5000
10/10 - 0s - 8ms/step - loss: 2.3782e-08
Epoch 2951/5000
10/10 - 0s - 10ms/step - loss: 1.4149e-08
Epoch 2952/5000
10/10 - 0s - 8ms/step - loss: 6.2647e-09
Epoch 2953/5000
10/10 - 0s - 9ms/step - loss: 2.0175e-09
Epoch 2954/5000
10/10 - 0s - 8ms/step - loss: 1.9893e-09
Epoch 2955/5000
10/10 - 0s - 8ms/step - loss: 7.5323e-09
Epoch 2956/5000
10/10 - 0s - 9ms/step - loss: 8.3601e-08
Epoch 2957/5000
10/10 - 0s - 9ms/step - loss: 2.9555e-07
Epoch 2958/5000
10/10 - 0s - 9ms/step - loss: 6.2607e-08
Epoch 2959/5000
10/10 - 0s - 17ms/step - loss: 2.1650e-08
Epoch 2960/5000
10/10 - 0s - 8ms/step - loss: 8.2008e-09
Epoch 2961/5000
10/10 - 0s - 9ms/step - loss: 3.9935e-09
Epoch 2962/5000
10/10 - 0s - 18ms/step - loss: 1.1491e-09
Epoch 2963/5000
10/10 - 0s - 17ms/step - loss: 6.0566e-10
Epoch 2964/5000
10/10 - 0s - 9ms/step - loss: 4.4515e-09
Epoch 2965/5000
10/10 - 0s - 9ms/step - loss: 1.0673e-08
Epoch 2966/5000
10/10 - 0s - 17ms/step - loss: 1.4823e-08
Epoch 2967/5000
10/10 - 0s - 9ms/step - loss: 2.9677e-08
Epoch 2968/5000
10/10 - 0s - 9ms/step - loss: 1.9239e-07
Epoch 2969/5000
10/10 - 0s - 9ms/step - loss: 7.2554e-08
Epoch 2970/5000
10/10 - 0s - 9ms/step - loss: 3.3686e-08
Epoch 2971/5000
10/10 - 0s - 9ms/step - loss: 1.2281e-08
Epoch 2972/5000
10/10 - 0s - 9ms/step - loss: 2.0493e-09
Epoch 2973/5000
10/10 - 0s - 9ms/step - loss: 2.3234e-09
Epoch 2974/5000
10/10 - 0s - 9ms/step - loss: 3.1018e-10
Epoch 2975/5000
10/10 - 0s - 9ms/step - loss: 2.8543e-11
Epoch 2976/5000
10/10 - 0s - 10ms/step - loss: 1.2708e-09
Epoch 2977/5000
10/10 - 0s - 8ms/step - loss: 5.7208e-08
Epoch 2978/5000
10/10 - 0s - 9ms/step - loss: 5.1499e-07
Epoch 2979/5000
10/10 - 0s - 8ms/step - loss: 1.3567e-07
Epoch 2980/5000
10/10 - 0s - 8ms/step - loss: 5.6958e-08
Epoch 2981/5000
10/10 - 0s - 9ms/step - loss: 1.4875e-08
Epoch 2982/5000
10/10 - 0s - 9ms/step - loss: 8.0313e-09
Epoch 2983/5000
10/10 - 0s - 8ms/step - loss: 1.0907e-09
Epoch 2984/5000
10/10 - 0s - 8ms/step - loss: 6.2633e-10
Epoch 2985/5000
10/10 - 0s - 9ms/step - loss: 3.6607e-10
Epoch 2986/5000
10/10 - 0s - 9ms/step - loss: 3.7802e-10
Epoch 2987/5000
10/10 - 0s - 9ms/step - loss: 1.4019e-10
Epoch 2988/5000
10/10 - 0s - 8ms/step - loss: 4.6159e-10
Epoch 2989/5000
10/10 - 0s - 8ms/step - loss: 8.2877e-10
Epoch 2990/5000
10/10 - 0s - 8ms/step - loss: 3.4046e-10
Epoch 2991/5000
10/10 - 0s - 8ms/step - loss: 1.3404e-10
Epoch 2992/5000
10/10 - 0s - 10ms/step - loss: 2.0181e-10
Epoch 2993/5000
10/10 - 0s - 9ms/step - loss: 2.4029e-09
Epoch 2994/5000
10/10 - 0s - 9ms/step - loss: 2.4927e-08
Epoch 2995/5000
10/10 - 0s - 8ms/step - loss: 2.8969e-07
Epoch 2996/5000
10/10 - 0s - 8ms/step - loss: 1.1315e-07
Epoch 2997/5000
10/10 - 0s - 8ms/step - loss: 3.7310e-08
Epoch 2998/5000
10/10 - 0s - 10ms/step - loss: 1.3770e-08
Epoch 2999/5000
10/10 - 0s - 16ms/step - loss: 7.6534e-09
Epoch 3000/5000
10/10 - 0s - 9ms/step - loss: 3.1078e-09
Epoch 3001/5000
10/10 - 0s - 8ms/step - loss: 2.8101e-09
Epoch 3002/5000
10/10 - 0s - 9ms/step - loss: 3.5721e-10
Epoch 3003/5000
10/10 - 0s - 8ms/step - loss: 2.5096e-10
Epoch 3004/5000
10/10 - 0s - 10ms/step - loss: 7.0462e-10
Epoch 3005/5000
10/10 - 0s - 8ms/step - loss: 5.2590e-10
Epoch 3006/5000
10/10 - 0s - 9ms/step - loss: 2.5543e-08
Epoch 3007/5000
10/10 - 0s - 9ms/step - loss: 3.2881e-07
Epoch 3008/5000
10/10 - 0s - 9ms/step - loss: 1.2099e-07
Epoch 3009/5000
10/10 - 0s - 9ms/step - loss: 3.5661e-08
Epoch 3010/5000
10/10 - 0s - 9ms/step - loss: 1.1417e-08
Epoch 3011/5000
10/10 - 0s - 8ms/step - loss: 4.1971e-09
Epoch 3012/5000
10/10 - 0s - 9ms/step - loss: 1.8538e-09
Epoch 3013/5000
10/10 - 0s - 8ms/step - loss: 1.5824e-09
Epoch 3014/5000
10/10 - 0s - 9ms/step - loss: 2.8911e-10
Epoch 3015/5000
10/10 - 0s - 9ms/step - loss: 8.6986e-10
Epoch 3016/5000
10/10 - 0s - 9ms/step - loss: 1.9706e-10
Epoch 3017/5000
10/10 - 0s - 9ms/step - loss: 1.1560e-09
Epoch 3018/5000
10/10 - 0s - 8ms/step - loss: 3.3229e-09
Epoch 3019/5000
10/10 - 0s - 9ms/step - loss: 4.6271e-08
Epoch 3020/5000
10/10 - 0s - 8ms/step - loss: 3.9757e-07
Epoch 3021/5000
10/10 - 0s - 9ms/step - loss: 9.1540e-08
Epoch 3022/5000
10/10 - 0s - 9ms/step - loss: 3.3832e-08
Epoch 3023/5000
10/10 - 0s - 10ms/step - loss: 1.7558e-08
Epoch 3024/5000
10/10 - 0s - 14ms/step - loss: 1.0237e-08
Epoch 3025/5000
10/10 - 0s - 12ms/step - loss: 4.1997e-09
Epoch 3026/5000
10/10 - 0s - 9ms/step - loss: 2.2274e-09
Epoch 3027/5000
10/10 - 0s - 8ms/step - loss: 8.0126e-10
Epoch 3028/5000
10/10 - 0s - 20ms/step - loss: 3.9938e-10
Epoch 3029/5000
10/10 - 0s - 7ms/step - loss: 4.7197e-11
Epoch 3030/5000
10/10 - 0s - 8ms/step - loss: 7.2425e-11
Epoch 3031/5000
10/10 - 0s - 9ms/step - loss: 8.8924e-11
Epoch 3032/5000
10/10 - 0s - 8ms/step - loss: 1.3269e-09
Epoch 3033/5000
10/10 - 0s - 8ms/step - loss: 3.8771e-08
Epoch 3034/5000
10/10 - 0s - 9ms/step - loss: 3.6069e-07
Epoch 3035/5000
10/10 - 0s - 9ms/step - loss: 8.3600e-08
Epoch 3036/5000
10/10 - 0s - 8ms/step - loss: 2.7151e-08
Epoch 3037/5000
10/10 - 0s - 9ms/step - loss: 1.3697e-08
Epoch 3038/5000
10/10 - 0s - 8ms/step - loss: 4.8483e-09
Epoch 3039/5000
10/10 - 0s - 8ms/step - loss: 1.6255e-09
Epoch 3040/5000
10/10 - 0s - 8ms/step - loss: 3.8582e-10
Epoch 3041/5000
10/10 - 0s - 18ms/step - loss: 2.7122e-10
Epoch 3042/5000
10/10 - 0s - 8ms/step - loss: 8.5424e-10
Epoch 3043/5000
10/10 - 0s - 10ms/step - loss: 8.8920e-10
Epoch 3044/5000
10/10 - 0s - 9ms/step - loss: 2.9199e-10
Epoch 3045/5000
10/10 - 0s - 8ms/step - loss: 4.2832e-09
Epoch 3046/5000
10/10 - 0s - 11ms/step - loss: 1.0874e-07
Epoch 3047/5000
10/10 - 0s - 17ms/step - loss: 2.9619e-07
Epoch 3048/5000
10/10 - 0s - 8ms/step - loss: 7.0125e-08
Epoch 3049/5000
10/10 - 0s - 8ms/step - loss: 2.8416e-08
Epoch 3050/5000
10/10 - 0s - 9ms/step - loss: 1.1328e-08
Epoch 3051/5000
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Epoch 3052/5000
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Epoch 3053/5000
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Epoch 3054/5000
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Epoch 3055/5000
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Epoch 3056/5000
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Epoch 3057/5000
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Epoch 3058/5000
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Epoch 3059/5000
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Epoch 3060/5000
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Epoch 3061/5000
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Epoch 3062/5000
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Epoch 3063/5000
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Epoch 3064/5000
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Epoch 3065/5000
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Epoch 3066/5000
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Epoch 3067/5000
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Epoch 3068/5000
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Epoch 3069/5000
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Epoch 3070/5000
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Epoch 3071/5000
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Epoch 3072/5000
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Epoch 3073/5000
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Epoch 3074/5000
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Epoch 3075/5000
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Epoch 3076/5000
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Epoch 3077/5000
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Epoch 3078/5000
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Epoch 3079/5000
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Epoch 3080/5000
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Epoch 3081/5000
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Epoch 3082/5000
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Epoch 3083/5000
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Epoch 3084/5000
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Epoch 3085/5000
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Epoch 3086/5000
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Epoch 3087/5000
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Epoch 3088/5000
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Epoch 3089/5000
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Epoch 3090/5000
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Epoch 3091/5000
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Epoch 3092/5000
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Epoch 3093/5000
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Epoch 3094/5000
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Epoch 3095/5000
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Epoch 3096/5000
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Epoch 3097/5000
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Epoch 3098/5000
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Epoch 3099/5000
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Epoch 3100/5000
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Epoch 3101/5000
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Epoch 3102/5000
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Epoch 3103/5000
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Epoch 3104/5000
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Epoch 3105/5000
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Epoch 3106/5000
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Epoch 3107/5000
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Epoch 3108/5000
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Epoch 3109/5000
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Epoch 3110/5000
10/10 - 0s - 9ms/step - loss: 1.5867e-08
Epoch 3111/5000
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Epoch 3112/5000
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Epoch 3113/5000
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Epoch 3114/5000
10/10 - 0s - 8ms/step - loss: 8.1672e-09
Epoch 3115/5000
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Epoch 3116/5000
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Epoch 3117/5000
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Epoch 3118/5000
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Epoch 3119/5000
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Epoch 3120/5000
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Epoch 3121/5000
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Epoch 3122/5000
10/10 - 0s - 10ms/step - loss: 5.3905e-08
Epoch 3123/5000
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Epoch 3124/5000
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Epoch 3125/5000
10/10 - 0s - 9ms/step - loss: 9.1090e-10
Epoch 3126/5000
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Epoch 3127/5000
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Epoch 3128/5000
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Epoch 3129/5000
10/10 - 0s - 8ms/step - loss: 2.2616e-09
Epoch 3130/5000
10/10 - 0s - 10ms/step - loss: 1.8924e-08
Epoch 3131/5000
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Epoch 3132/5000
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Epoch 3133/5000
10/10 - 0s - 9ms/step - loss: 3.7295e-08
Epoch 3134/5000
10/10 - 0s - 9ms/step - loss: 9.9614e-09
Epoch 3135/5000
10/10 - 0s - 8ms/step - loss: 7.5645e-09
Epoch 3136/5000
10/10 - 0s - 8ms/step - loss: 4.6933e-09
Epoch 3137/5000
10/10 - 0s - 9ms/step - loss: 6.2659e-10
Epoch 3138/5000
10/10 - 0s - 8ms/step - loss: 3.4871e-09
Epoch 3139/5000
10/10 - 0s - 9ms/step - loss: 5.4817e-08
Epoch 3140/5000
10/10 - 0s - 9ms/step - loss: 2.3055e-07
Epoch 3141/5000
10/10 - 0s - 8ms/step - loss: 4.1996e-08
Epoch 3142/5000
10/10 - 0s - 13ms/step - loss: 1.8016e-08
Epoch 3143/5000
10/10 - 0s - 14ms/step - loss: 9.2359e-09
Epoch 3144/5000
10/10 - 0s - 15ms/step - loss: 4.0455e-09
Epoch 3145/5000
10/10 - 0s - 9ms/step - loss: 1.7883e-09
Epoch 3146/5000
10/10 - 0s - 7ms/step - loss: 6.8027e-09
Epoch 3147/5000
10/10 - 0s - 10ms/step - loss: 1.5475e-08
Epoch 3148/5000
10/10 - 0s - 15ms/step - loss: 6.7159e-08
Epoch 3149/5000
10/10 - 0s - 9ms/step - loss: 1.8939e-07
Epoch 3150/5000
10/10 - 0s - 9ms/step - loss: 2.8827e-08
Epoch 3151/5000
10/10 - 0s - 9ms/step - loss: 1.5794e-08
Epoch 3152/5000
10/10 - 0s - 9ms/step - loss: 1.2413e-08
Epoch 3153/5000
10/10 - 0s - 10ms/step - loss: 4.7282e-09
Epoch 3154/5000
10/10 - 0s - 9ms/step - loss: 2.1765e-08
Epoch 3155/5000
10/10 - 0s - 9ms/step - loss: 2.5355e-08
Epoch 3156/5000
10/10 - 0s - 9ms/step - loss: 3.9291e-08
Epoch 3157/5000
10/10 - 0s - 9ms/step - loss: 5.0324e-08
Epoch 3158/5000
10/10 - 0s - 10ms/step - loss: 3.5749e-08
Epoch 3159/5000
10/10 - 0s - 8ms/step - loss: 1.2639e-08
Epoch 3160/5000
10/10 - 0s - 8ms/step - loss: 2.7688e-08
Epoch 3161/5000
10/10 - 0s - 8ms/step - loss: 1.3005e-07
Epoch 3162/5000
10/10 - 0s - 9ms/step - loss: 9.1122e-08
Epoch 3163/5000
10/10 - 0s - 9ms/step - loss: 3.2816e-08
Epoch 3164/5000
10/10 - 0s - 9ms/step - loss: 8.2315e-09
Epoch 3165/5000
10/10 - 0s - 10ms/step - loss: 2.1440e-08
Epoch 3166/5000
10/10 - 0s - 8ms/step - loss: 6.3548e-09
Epoch 3167/5000
10/10 - 0s - 9ms/step - loss: 3.5163e-10
Epoch 3168/5000
10/10 - 0s - 10ms/step - loss: 1.4133e-10
Epoch 3169/5000
10/10 - 0s - 8ms/step - loss: 4.5979e-09
Epoch 3170/5000
10/10 - 0s - 8ms/step - loss: 2.2825e-07
Epoch 3171/5000
10/10 - 0s - 9ms/step - loss: 3.5098e-07
Epoch 3172/5000
10/10 - 0s - 9ms/step - loss: 9.6635e-08
Epoch 3173/5000
10/10 - 0s - 9ms/step - loss: 2.6748e-08
Epoch 3174/5000
10/10 - 0s - 9ms/step - loss: 1.6830e-08
Epoch 3175/5000
10/10 - 0s - 10ms/step - loss: 5.0523e-09
Epoch 3176/5000
10/10 - 0s - 8ms/step - loss: 1.4757e-09
Epoch 3177/5000
10/10 - 0s - 8ms/step - loss: 6.2067e-10
Epoch 3178/5000
10/10 - 0s - 9ms/step - loss: 1.2054e-10
Epoch 3179/5000
10/10 - 0s - 8ms/step - loss: 5.3991e-10
Epoch 3180/5000
10/10 - 0s - 8ms/step - loss: 9.6270e-11
Epoch 3181/5000
10/10 - 0s - 9ms/step - loss: 9.9012e-10
Epoch 3182/5000
10/10 - 0s - 9ms/step - loss: 2.2323e-10
Epoch 3183/5000
10/10 - 0s - 9ms/step - loss: 8.8885e-10
Epoch 3184/5000
10/10 - 0s - 9ms/step - loss: 9.4840e-10
Epoch 3185/5000
10/10 - 0s - 9ms/step - loss: 8.9597e-09
Epoch 3186/5000
10/10 - 0s - 8ms/step - loss: 1.1068e-07
Epoch 3187/5000
10/10 - 0s - 9ms/step - loss: 1.9956e-07
Epoch 3188/5000
10/10 - 0s - 17ms/step - loss: 4.1186e-08
Epoch 3189/5000
10/10 - 0s - 9ms/step - loss: 1.7300e-08
Epoch 3190/5000
10/10 - 0s - 17ms/step - loss: 5.4444e-09
Epoch 3191/5000
10/10 - 0s - 9ms/step - loss: 1.3724e-09
Epoch 3192/5000
10/10 - 0s - 9ms/step - loss: 4.2849e-10
Epoch 3193/5000
10/10 - 0s - 10ms/step - loss: 2.5959e-09
Epoch 3194/5000
10/10 - 0s - 9ms/step - loss: 1.3329e-08
Epoch 3195/5000
10/10 - 0s - 8ms/step - loss: 4.4242e-08
Epoch 3196/5000
10/10 - 0s - 9ms/step - loss: 1.6442e-07
Epoch 3197/5000
10/10 - 0s - 8ms/step - loss: 4.6912e-08
Epoch 3198/5000
10/10 - 0s - 9ms/step - loss: 2.6345e-08
Epoch 3199/5000
10/10 - 0s - 9ms/step - loss: 6.8315e-09
Epoch 3200/5000
10/10 - 0s - 9ms/step - loss: 4.6821e-09
Epoch 3201/5000
10/10 - 0s - 9ms/step - loss: 3.1212e-10
Epoch 3202/5000
10/10 - 0s - 20ms/step - loss: 7.8065e-09
Epoch 3203/5000
10/10 - 0s - 8ms/step - loss: 1.2656e-07
Epoch 3204/5000
10/10 - 0s - 9ms/step - loss: 1.9877e-07
Epoch 3205/5000
10/10 - 0s - 8ms/step - loss: 5.5675e-08
Epoch 3206/5000
10/10 - 0s - 9ms/step - loss: 2.1318e-08
Epoch 3207/5000
10/10 - 0s - 9ms/step - loss: 6.1334e-09
Epoch 3208/5000
10/10 - 0s - 8ms/step - loss: 8.9666e-10
Epoch 3209/5000
10/10 - 0s - 10ms/step - loss: 1.9989e-09
Epoch 3210/5000
10/10 - 0s - 8ms/step - loss: 1.0898e-09
Epoch 3211/5000
10/10 - 0s - 9ms/step - loss: 1.1160e-10
Epoch 3212/5000
10/10 - 0s - 8ms/step - loss: 3.4308e-09
Epoch 3213/5000
10/10 - 0s - 8ms/step - loss: 4.7298e-08
Epoch 3214/5000
10/10 - 0s - 8ms/step - loss: 2.8569e-07
Epoch 3215/5000
10/10 - 0s - 8ms/step - loss: 6.3169e-08
Epoch 3216/5000
10/10 - 0s - 10ms/step - loss: 2.3333e-08
Epoch 3217/5000
10/10 - 0s - 8ms/step - loss: 6.3388e-09
Epoch 3218/5000
10/10 - 0s - 8ms/step - loss: 2.2552e-09
Epoch 3219/5000
10/10 - 0s - 9ms/step - loss: 8.9549e-10
Epoch 3220/5000
10/10 - 0s - 9ms/step - loss: 4.1458e-09
Epoch 3221/5000
10/10 - 0s - 9ms/step - loss: 2.1407e-09
Epoch 3222/5000
10/10 - 0s - 7ms/step - loss: 3.6063e-10
Epoch 3223/5000
10/10 - 0s - 9ms/step - loss: 3.0454e-10
Epoch 3224/5000
10/10 - 0s - 10ms/step - loss: 3.1383e-10
Epoch 3225/5000
10/10 - 0s - 7ms/step - loss: 5.6972e-09
Epoch 3226/5000
10/10 - 0s - 9ms/step - loss: 2.9444e-07
Epoch 3227/5000
10/10 - 0s - 9ms/step - loss: 4.6374e-07
Epoch 3228/5000
10/10 - 0s - 18ms/step - loss: 9.4425e-08
Epoch 3229/5000
10/10 - 0s - 10ms/step - loss: 4.8860e-08
Epoch 3230/5000
10/10 - 0s - 10ms/step - loss: 1.4010e-08
Epoch 3231/5000
10/10 - 0s - 8ms/step - loss: 6.5754e-09
Epoch 3232/5000
10/10 - 0s - 9ms/step - loss: 2.6062e-09
Epoch 3233/5000
10/10 - 0s - 9ms/step - loss: 9.8083e-10
Epoch 3234/5000
10/10 - 0s - 8ms/step - loss: 1.8546e-10
Epoch 3235/5000
10/10 - 0s - 8ms/step - loss: 1.8999e-10
Epoch 3236/5000
10/10 - 0s - 8ms/step - loss: 5.3886e-10
Epoch 3237/5000
10/10 - 0s - 8ms/step - loss: 4.3597e-10
Epoch 3238/5000
10/10 - 0s - 8ms/step - loss: 9.1947e-10
Epoch 3239/5000
10/10 - 0s - 10ms/step - loss: 2.6498e-11
Epoch 3240/5000
10/10 - 0s - 9ms/step - loss: 9.3942e-11
Epoch 3241/5000
10/10 - 0s - 8ms/step - loss: 4.0452e-10
Epoch 3242/5000
10/10 - 0s - 9ms/step - loss: 1.7217e-10
Epoch 3243/5000
10/10 - 0s - 9ms/step - loss: 1.3625e-09
Epoch 3244/5000
10/10 - 0s - 9ms/step - loss: 6.6970e-09
Epoch 3245/5000
10/10 - 0s - 9ms/step - loss: 1.5199e-08
Epoch 3246/5000
10/10 - 0s - 9ms/step - loss: 7.1833e-08
Epoch 3247/5000
10/10 - 0s - 8ms/step - loss: 2.2522e-07
Epoch 3248/5000
10/10 - 0s - 9ms/step - loss: 4.1232e-08
Epoch 3249/5000
10/10 - 0s - 10ms/step - loss: 1.6700e-08
Epoch 3250/5000
10/10 - 0s - 9ms/step - loss: 8.2826e-09
Epoch 3251/5000
10/10 - 0s - 8ms/step - loss: 7.1964e-09
Epoch 3252/5000
10/10 - 0s - 9ms/step - loss: 1.2093e-09
Epoch 3253/5000
10/10 - 0s - 9ms/step - loss: 1.2809e-09
Epoch 3254/5000
10/10 - 0s - 10ms/step - loss: 4.0089e-11
Epoch 3255/5000
10/10 - 0s - 8ms/step - loss: 2.1644e-10
Epoch 3256/5000
10/10 - 0s - 8ms/step - loss: 1.0381e-08
Epoch 3257/5000
10/10 - 0s - 8ms/step - loss: 2.8145e-07
Epoch 3258/5000
10/10 - 0s - 9ms/step - loss: 2.8885e-07
Epoch 3259/5000
10/10 - 0s - 8ms/step - loss: 7.3016e-08
Epoch 3260/5000
10/10 - 0s - 9ms/step - loss: 2.0990e-08
Epoch 3261/5000
10/10 - 0s - 9ms/step - loss: 1.1432e-08
Epoch 3262/5000
10/10 - 0s - 11ms/step - loss: 4.5615e-09
Epoch 3263/5000
10/10 - 0s - 14ms/step - loss: 8.1858e-10
Epoch 3264/5000
10/10 - 0s - 10ms/step - loss: 3.1220e-10
Epoch 3265/5000
10/10 - 0s - 9ms/step - loss: 1.6044e-10
Epoch 3266/5000
10/10 - 0s - 8ms/step - loss: 4.4729e-11
Epoch 3267/5000
10/10 - 0s - 8ms/step - loss: 3.5642e-11
Epoch 3268/5000
10/10 - 0s - 7ms/step - loss: 9.5352e-10
Epoch 3269/5000
10/10 - 0s - 8ms/step - loss: 8.7234e-10
Epoch 3270/5000
10/10 - 0s - 10ms/step - loss: 1.0797e-09
Epoch 3271/5000
10/10 - 0s - 10ms/step - loss: 3.3153e-10
Epoch 3272/5000
10/10 - 0s - 8ms/step - loss: 7.2490e-10
Epoch 3273/5000
10/10 - 0s - 8ms/step - loss: 1.0145e-08
Epoch 3274/5000
10/10 - 0s - 10ms/step - loss: 4.1572e-07
Epoch 3275/5000
10/10 - 0s - 9ms/step - loss: 2.9341e-07
Epoch 3276/5000
10/10 - 0s - 9ms/step - loss: 7.2222e-08
Epoch 3277/5000
10/10 - 0s - 8ms/step - loss: 3.9287e-08
Epoch 3278/5000
10/10 - 0s - 8ms/step - loss: 1.0541e-08
Epoch 3279/5000
10/10 - 0s - 9ms/step - loss: 4.2977e-09
Epoch 3280/5000
10/10 - 0s - 9ms/step - loss: 6.1157e-10
Epoch 3281/5000
10/10 - 0s - 8ms/step - loss: 2.4006e-10
Epoch 3282/5000
10/10 - 0s - 9ms/step - loss: 1.5043e-10
Epoch 3283/5000
10/10 - 0s - 8ms/step - loss: 3.6356e-10
Epoch 3284/5000
10/10 - 0s - 9ms/step - loss: 7.2869e-10
Epoch 3285/5000
10/10 - 0s - 9ms/step - loss: 7.3203e-10
Epoch 3286/5000
10/10 - 0s - 10ms/step - loss: 2.4195e-10
Epoch 3287/5000
10/10 - 0s - 8ms/step - loss: 7.2089e-10
Epoch 3288/5000
10/10 - 0s - 8ms/step - loss: 1.1879e-09
Epoch 3289/5000
10/10 - 0s - 9ms/step - loss: 4.1058e-09
Epoch 3290/5000
10/10 - 0s - 9ms/step - loss: 2.5030e-09
Epoch 3291/5000
10/10 - 0s - 8ms/step - loss: 1.1216e-08
Epoch 3292/5000
10/10 - 0s - 8ms/step - loss: 8.5808e-08
Epoch 3293/5000
10/10 - 0s - 18ms/step - loss: 1.7753e-07
Epoch 3294/5000
10/10 - 0s - 9ms/step - loss: 3.5732e-08
Epoch 3295/5000
10/10 - 0s - 8ms/step - loss: 1.2788e-08
Epoch 3296/5000
10/10 - 0s - 8ms/step - loss: 8.3123e-09
Epoch 3297/5000
10/10 - 0s - 10ms/step - loss: 6.7530e-09
Epoch 3298/5000
10/10 - 0s - 10ms/step - loss: 1.3322e-09
Epoch 3299/5000
10/10 - 0s - 9ms/step - loss: 2.3035e-10
Epoch 3300/5000
10/10 - 0s - 10ms/step - loss: 2.4212e-09
Epoch 3301/5000
10/10 - 0s - 9ms/step - loss: 4.6731e-08
Epoch 3302/5000
10/10 - 0s - 8ms/step - loss: 3.5912e-07
Epoch 3303/5000
10/10 - 0s - 10ms/step - loss: 8.6464e-08
Epoch 3304/5000
10/10 - 0s - 8ms/step - loss: 3.3747e-08
Epoch 3305/5000
10/10 - 0s - 10ms/step - loss: 1.7016e-08
Epoch 3306/5000
10/10 - 0s - 8ms/step - loss: 7.6884e-09
Epoch 3307/5000
10/10 - 0s - 9ms/step - loss: 3.1754e-09
Epoch 3308/5000
10/10 - 0s - 10ms/step - loss: 1.4019e-09
Epoch 3309/5000
10/10 - 0s - 17ms/step - loss: 3.7487e-10
Epoch 3310/5000
10/10 - 0s - 8ms/step - loss: 6.0266e-10
Epoch 3311/5000
10/10 - 0s - 8ms/step - loss: 8.1198e-10
Epoch 3312/5000
10/10 - 0s - 9ms/step - loss: 2.0733e-10
Epoch 3313/5000
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Epoch 3314/5000
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Epoch 3315/5000
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Epoch 3316/5000
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Epoch 3317/5000
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Epoch 3318/5000
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Epoch 3319/5000
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Epoch 3320/5000
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Epoch 3321/5000
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Epoch 3322/5000
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Epoch 3323/5000
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Epoch 3324/5000
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Epoch 3325/5000
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Epoch 3326/5000
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Epoch 3327/5000
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Epoch 3328/5000
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Epoch 3329/5000
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Epoch 3330/5000
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Epoch 3331/5000
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Epoch 3332/5000
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Epoch 3333/5000
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Epoch 3334/5000
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Epoch 3335/5000
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Epoch 3336/5000
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Epoch 3337/5000
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Epoch 3338/5000
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Epoch 3339/5000
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Epoch 3340/5000
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Epoch 3341/5000
10/10 - 0s - 8ms/step - loss: 9.2913e-10
Epoch 3342/5000
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Epoch 3343/5000
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Epoch 3344/5000
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Epoch 3345/5000
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Epoch 3346/5000
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Epoch 3347/5000
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Epoch 3348/5000
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Epoch 3349/5000
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Epoch 3350/5000
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Epoch 3351/5000
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Epoch 3352/5000
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Epoch 3353/5000
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Epoch 3354/5000
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Epoch 3355/5000
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Epoch 3356/5000
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Epoch 3357/5000
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Epoch 3358/5000
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Epoch 3359/5000
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Epoch 3360/5000
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Epoch 3361/5000
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Epoch 3362/5000
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Epoch 3363/5000
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Epoch 3364/5000
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Epoch 3365/5000
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Epoch 3366/5000
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Epoch 3367/5000
10/10 - 0s - 8ms/step - loss: 9.9214e-09
Epoch 3368/5000
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Epoch 3369/5000
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Epoch 3370/5000
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Epoch 3371/5000
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Epoch 3372/5000
10/10 - 0s - 10ms/step - loss: 6.3835e-09
Epoch 3373/5000
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Epoch 3374/5000
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Epoch 3375/5000
10/10 - 0s - 16ms/step - loss: 9.3912e-10
Epoch 3376/5000
10/10 - 0s - 9ms/step - loss: 2.7577e-09
Epoch 3377/5000
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Epoch 3378/5000
10/10 - 0s - 8ms/step - loss: 1.3521e-07
Epoch 3379/5000
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Epoch 3380/5000
10/10 - 0s - 10ms/step - loss: 4.0382e-08
Epoch 3381/5000
10/10 - 0s - 8ms/step - loss: 1.5001e-08
Epoch 3382/5000
10/10 - 0s - 10ms/step - loss: 5.9432e-09
Epoch 3383/5000
10/10 - 0s - 8ms/step - loss: 1.8512e-09
Epoch 3384/5000
10/10 - 0s - 10ms/step - loss: 9.7049e-10
Epoch 3385/5000
10/10 - 0s - 9ms/step - loss: 1.3636e-09
Epoch 3386/5000
10/10 - 0s - 8ms/step - loss: 3.5194e-08
Epoch 3387/5000
10/10 - 0s - 9ms/step - loss: 1.7783e-07
Epoch 3388/5000
10/10 - 0s - 10ms/step - loss: 4.4324e-08
Epoch 3389/5000
10/10 - 0s - 8ms/step - loss: 2.6196e-08
Epoch 3390/5000
10/10 - 0s - 9ms/step - loss: 1.6041e-08
Epoch 3391/5000
10/10 - 0s - 9ms/step - loss: 2.5023e-09
Epoch 3392/5000
10/10 - 0s - 10ms/step - loss: 6.4437e-10
Epoch 3393/5000
10/10 - 0s - 8ms/step - loss: 7.0641e-09
Epoch 3394/5000
10/10 - 0s - 8ms/step - loss: 5.4582e-08
Epoch 3395/5000
10/10 - 0s - 9ms/step - loss: 1.5654e-07
Epoch 3396/5000
10/10 - 0s - 8ms/step - loss: 2.8059e-08
Epoch 3397/5000
10/10 - 0s - 8ms/step - loss: 1.3938e-08
Epoch 3398/5000
10/10 - 0s - 10ms/step - loss: 4.4962e-09
Epoch 3399/5000
10/10 - 0s - 10ms/step - loss: 1.8233e-08
Epoch 3400/5000
10/10 - 0s - 8ms/step - loss: 2.8367e-08
Epoch 3401/5000
10/10 - 0s - 8ms/step - loss: 3.5260e-08
Epoch 3402/5000
10/10 - 0s - 10ms/step - loss: 7.9824e-08
Epoch 3403/5000
10/10 - 0s - 10ms/step - loss: 7.3013e-08
Epoch 3404/5000
10/10 - 0s - 9ms/step - loss: 5.6573e-09
Epoch 3405/5000
10/10 - 0s - 9ms/step - loss: 2.6657e-08
Epoch 3406/5000
10/10 - 0s - 9ms/step - loss: 2.6772e-08
Epoch 3407/5000
10/10 - 0s - 8ms/step - loss: 2.9906e-08
Epoch 3408/5000
10/10 - 0s - 9ms/step - loss: 6.3425e-08
Epoch 3409/5000
10/10 - 0s - 9ms/step - loss: 7.6985e-08
Epoch 3410/5000
10/10 - 0s - 9ms/step - loss: 1.2405e-08
Epoch 3411/5000
10/10 - 0s - 9ms/step - loss: 1.3866e-08
Epoch 3412/5000
10/10 - 0s - 8ms/step - loss: 3.1429e-08
Epoch 3413/5000
10/10 - 0s - 9ms/step - loss: 6.1387e-08
Epoch 3414/5000
10/10 - 0s - 9ms/step - loss: 8.7698e-08
Epoch 3415/5000
10/10 - 0s - 9ms/step - loss: 9.7031e-09
Epoch 3416/5000
10/10 - 0s - 9ms/step - loss: 1.4607e-08
Epoch 3417/5000
10/10 - 0s - 7ms/step - loss: 2.1962e-08
Epoch 3418/5000
10/10 - 0s - 8ms/step - loss: 4.8767e-08
Epoch 3419/5000
10/10 - 0s - 9ms/step - loss: 1.0909e-07
Epoch 3420/5000
10/10 - 0s - 18ms/step - loss: 2.0169e-08
Epoch 3421/5000
10/10 - 0s - 10ms/step - loss: 1.8013e-08
Epoch 3422/5000
10/10 - 0s - 9ms/step - loss: 1.2536e-08
Epoch 3423/5000
10/10 - 0s - 8ms/step - loss: 8.6251e-09
Epoch 3424/5000
10/10 - 0s - 18ms/step - loss: 5.3034e-08
Epoch 3425/5000
10/10 - 0s - 9ms/step - loss: 1.9008e-07
Epoch 3426/5000
10/10 - 0s - 8ms/step - loss: 3.1996e-08
Epoch 3427/5000
10/10 - 0s - 9ms/step - loss: 1.6524e-08
Epoch 3428/5000
10/10 - 0s - 9ms/step - loss: 7.8403e-09
Epoch 3429/5000
10/10 - 0s - 18ms/step - loss: 2.7370e-09
Epoch 3430/5000
10/10 - 0s - 17ms/step - loss: 3.0342e-09
Epoch 3431/5000
10/10 - 0s - 12ms/step - loss: 4.3200e-10
Epoch 3432/5000
10/10 - 0s - 9ms/step - loss: 5.0742e-09
Epoch 3433/5000
10/10 - 0s - 8ms/step - loss: 6.9567e-08
Epoch 3434/5000
10/10 - 0s - 10ms/step - loss: 3.8884e-07
Epoch 3435/5000
10/10 - 0s - 9ms/step - loss: 9.2460e-08
Epoch 3436/5000
10/10 - 0s - 8ms/step - loss: 3.7623e-08
Epoch 3437/5000
10/10 - 0s - 9ms/step - loss: 1.0733e-08
Epoch 3438/5000
10/10 - 0s - 8ms/step - loss: 3.9257e-09
Epoch 3439/5000
10/10 - 0s - 9ms/step - loss: 2.1782e-09
Epoch 3440/5000
10/10 - 0s - 8ms/step - loss: 1.3358e-09
Epoch 3441/5000
10/10 - 0s - 8ms/step - loss: 1.2580e-09
Epoch 3442/5000
10/10 - 0s - 8ms/step - loss: 1.3937e-09
Epoch 3443/5000
10/10 - 0s - 8ms/step - loss: 3.4223e-10
Epoch 3444/5000
10/10 - 0s - 8ms/step - loss: 5.0852e-10
Epoch 3445/5000
10/10 - 0s - 8ms/step - loss: 1.1891e-09
Epoch 3446/5000
10/10 - 0s - 10ms/step - loss: 4.6293e-10
Epoch 3447/5000
10/10 - 0s - 9ms/step - loss: 1.4396e-08
Epoch 3448/5000
10/10 - 0s - 10ms/step - loss: 1.7123e-07
Epoch 3449/5000
10/10 - 0s - 8ms/step - loss: 1.7866e-07
Epoch 3450/5000
10/10 - 0s - 9ms/step - loss: 5.1745e-08
Epoch 3451/5000
10/10 - 0s - 9ms/step - loss: 2.2265e-08
Epoch 3452/5000
10/10 - 0s - 8ms/step - loss: 8.6647e-09
Epoch 3453/5000
10/10 - 0s - 8ms/step - loss: 3.0527e-09
Epoch 3454/5000
10/10 - 0s - 10ms/step - loss: 2.9613e-09
Epoch 3455/5000
10/10 - 0s - 9ms/step - loss: 9.5481e-10
Epoch 3456/5000
10/10 - 0s - 9ms/step - loss: 8.2779e-10
Epoch 3457/5000
10/10 - 0s - 9ms/step - loss: 3.9893e-09
Epoch 3458/5000
10/10 - 0s - 9ms/step - loss: 2.3229e-08
Epoch 3459/5000
10/10 - 0s - 8ms/step - loss: 1.5386e-07
Epoch 3460/5000
10/10 - 0s - 9ms/step - loss: 9.7896e-08
Epoch 3461/5000
10/10 - 0s - 8ms/step - loss: 4.0465e-08
Epoch 3462/5000
10/10 - 0s - 9ms/step - loss: 1.8595e-08
Epoch 3463/5000
10/10 - 0s - 9ms/step - loss: 6.9999e-09
Epoch 3464/5000
10/10 - 0s - 8ms/step - loss: 1.0904e-08
Epoch 3465/5000
10/10 - 0s - 9ms/step - loss: 5.6300e-09
Epoch 3466/5000
10/10 - 0s - 10ms/step - loss: 1.2323e-10
Epoch 3467/5000
10/10 - 0s - 9ms/step - loss: 1.9219e-09
Epoch 3468/5000
10/10 - 0s - 9ms/step - loss: 3.6716e-08
Epoch 3469/5000
10/10 - 0s - 9ms/step - loss: 3.4406e-07
Epoch 3470/5000
10/10 - 0s - 9ms/step - loss: 9.2327e-08
Epoch 3471/5000
10/10 - 0s - 9ms/step - loss: 2.9726e-08
Epoch 3472/5000
10/10 - 0s - 9ms/step - loss: 1.2109e-08
Epoch 3473/5000
10/10 - 0s - 7ms/step - loss: 4.5956e-09
Epoch 3474/5000
10/10 - 0s - 7ms/step - loss: 1.4273e-09
Epoch 3475/5000
10/10 - 0s - 9ms/step - loss: 6.5641e-10
Epoch 3476/5000
10/10 - 0s - 8ms/step - loss: 7.4164e-10
Epoch 3477/5000
10/10 - 0s - 9ms/step - loss: 2.3453e-09
Epoch 3478/5000
10/10 - 0s - 9ms/step - loss: 5.5440e-10
Epoch 3479/5000
10/10 - 0s - 10ms/step - loss: 4.1048e-09
Epoch 3480/5000
10/10 - 0s - 8ms/step - loss: 7.1060e-09
Epoch 3481/5000
10/10 - 0s - 10ms/step - loss: 2.9585e-08
Epoch 3482/5000
10/10 - 0s - 10ms/step - loss: 2.8035e-07
Epoch 3483/5000
10/10 - 0s - 9ms/step - loss: 9.3625e-08
Epoch 3484/5000
10/10 - 0s - 8ms/step - loss: 2.7550e-08
Epoch 3485/5000
10/10 - 0s - 8ms/step - loss: 1.0337e-08
Epoch 3486/5000
10/10 - 0s - 8ms/step - loss: 3.3189e-09
Epoch 3487/5000
10/10 - 0s - 8ms/step - loss: 1.7951e-09
Epoch 3488/5000
10/10 - 0s - 10ms/step - loss: 4.5140e-09
Epoch 3489/5000
10/10 - 0s - 9ms/step - loss: 3.3617e-10
Epoch 3490/5000
10/10 - 0s - 9ms/step - loss: 4.1846e-10
Epoch 3491/5000
10/10 - 0s - 25ms/step - loss: 1.5848e-09
Epoch 3492/5000
10/10 - 0s - 8ms/step - loss: 3.5065e-09
Epoch 3493/5000
10/10 - 0s - 8ms/step - loss: 8.7917e-08
Epoch 3494/5000
10/10 - 0s - 11ms/step - loss: 3.4575e-07
Epoch 3495/5000
10/10 - 0s - 16ms/step - loss: 8.8083e-08
Epoch 3496/5000
10/10 - 0s - 9ms/step - loss: 3.2956e-08
Epoch 3497/5000
10/10 - 0s - 8ms/step - loss: 8.0953e-09
Epoch 3498/5000
10/10 - 0s - 10ms/step - loss: 3.1419e-09
Epoch 3499/5000
10/10 - 0s - 9ms/step - loss: 6.4435e-10
Epoch 3500/5000
10/10 - 0s - 9ms/step - loss: 2.3336e-10
Epoch 3501/5000
10/10 - 0s - 9ms/step - loss: 1.2849e-10
Epoch 3502/5000
10/10 - 0s - 8ms/step - loss: 5.0756e-10
Epoch 3503/5000
10/10 - 0s - 9ms/step - loss: 2.7066e-10
Epoch 3504/5000
10/10 - 0s - 9ms/step - loss: 1.4868e-09
Epoch 3505/5000
10/10 - 0s - 8ms/step - loss: 2.2206e-09
Epoch 3506/5000
10/10 - 0s - 9ms/step - loss: 2.4067e-08
Epoch 3507/5000
10/10 - 0s - 8ms/step - loss: 2.1147e-07
Epoch 3508/5000
10/10 - 0s - 10ms/step - loss: 8.4209e-08
Epoch 3509/5000
10/10 - 0s - 8ms/step - loss: 3.2051e-08
Epoch 3510/5000
10/10 - 0s - 10ms/step - loss: 1.6306e-08
Epoch 3511/5000
10/10 - 0s - 8ms/step - loss: 5.6678e-09
Epoch 3512/5000
10/10 - 0s - 8ms/step - loss: 1.0079e-09
Epoch 3513/5000
10/10 - 0s - 9ms/step - loss: 4.0838e-10
Epoch 3514/5000
10/10 - 0s - 10ms/step - loss: 6.8510e-10
Epoch 3515/5000
10/10 - 0s - 9ms/step - loss: 1.9978e-09
Epoch 3516/5000
10/10 - 0s - 9ms/step - loss: 1.5510e-08
Epoch 3517/5000
10/10 - 0s - 9ms/step - loss: 2.4544e-07
Epoch 3518/5000
10/10 - 0s - 10ms/step - loss: 1.7529e-07
Epoch 3519/5000
10/10 - 0s - 8ms/step - loss: 5.3015e-08
Epoch 3520/5000
10/10 - 0s - 8ms/step - loss: 1.3488e-08
Epoch 3521/5000
10/10 - 0s - 9ms/step - loss: 5.8867e-09
Epoch 3522/5000
10/10 - 0s - 9ms/step - loss: 2.2166e-09
Epoch 3523/5000
10/10 - 0s - 7ms/step - loss: 8.8233e-10
Epoch 3524/5000
10/10 - 0s - 9ms/step - loss: 8.7686e-10
Epoch 3525/5000
10/10 - 0s - 9ms/step - loss: 9.4480e-10
Epoch 3526/5000
10/10 - 0s - 9ms/step - loss: 1.4004e-10
Epoch 3527/5000
10/10 - 0s - 9ms/step - loss: 3.4386e-09
Epoch 3528/5000
10/10 - 0s - 9ms/step - loss: 1.2501e-08
Epoch 3529/5000
10/10 - 0s - 10ms/step - loss: 8.4544e-08
Epoch 3530/5000
10/10 - 0s - 9ms/step - loss: 2.0026e-07
Epoch 3531/5000
10/10 - 0s - 9ms/step - loss: 4.1053e-08
Epoch 3532/5000
10/10 - 0s - 9ms/step - loss: 1.7548e-08
Epoch 3533/5000
10/10 - 0s - 8ms/step - loss: 9.2169e-09
Epoch 3534/5000
10/10 - 0s - 9ms/step - loss: 4.1625e-09
Epoch 3535/5000
10/10 - 0s - 9ms/step - loss: 1.2593e-09
Epoch 3536/5000
10/10 - 0s - 8ms/step - loss: 2.4967e-09
Epoch 3537/5000
10/10 - 0s - 7ms/step - loss: 2.9778e-09
Epoch 3538/5000
10/10 - 0s - 9ms/step - loss: 1.0127e-08
Epoch 3539/5000
10/10 - 0s - 10ms/step - loss: 1.7851e-07
Epoch 3540/5000
10/10 - 0s - 10ms/step - loss: 2.1024e-07
Epoch 3541/5000
10/10 - 0s - 10ms/step - loss: 6.6255e-08
Epoch 3542/5000
10/10 - 0s - 9ms/step - loss: 2.4324e-08
Epoch 3543/5000
10/10 - 0s - 9ms/step - loss: 9.3350e-09
Epoch 3544/5000
10/10 - 0s - 7ms/step - loss: 3.2439e-09
Epoch 3545/5000
10/10 - 0s - 9ms/step - loss: 8.3579e-10
Epoch 3546/5000
10/10 - 0s - 9ms/step - loss: 9.4271e-10
Epoch 3547/5000
10/10 - 0s - 8ms/step - loss: 3.6220e-10
Epoch 3548/5000
10/10 - 0s - 8ms/step - loss: 7.4904e-10
Epoch 3549/5000
10/10 - 0s - 7ms/step - loss: 2.1248e-09
Epoch 3550/5000
10/10 - 0s - 10ms/step - loss: 2.2014e-09
Epoch 3551/5000
10/10 - 0s - 12ms/step - loss: 2.0885e-08
Epoch 3552/5000
10/10 - 0s - 13ms/step - loss: 2.9736e-07
Epoch 3553/5000
10/10 - 0s - 17ms/step - loss: 1.3680e-07
Epoch 3554/5000
10/10 - 0s - 17ms/step - loss: 4.6101e-08
Epoch 3555/5000
10/10 - 0s - 10ms/step - loss: 1.4734e-08
Epoch 3556/5000
10/10 - 0s - 9ms/step - loss: 4.4464e-09
Epoch 3557/5000
10/10 - 0s - 9ms/step - loss: 1.5160e-09
Epoch 3558/5000
10/10 - 0s - 9ms/step - loss: 1.2795e-09
Epoch 3559/5000
10/10 - 0s - 9ms/step - loss: 7.8463e-10
Epoch 3560/5000
10/10 - 0s - 9ms/step - loss: 2.0463e-09
Epoch 3561/5000
10/10 - 0s - 8ms/step - loss: 4.3089e-10
Epoch 3562/5000
10/10 - 0s - 9ms/step - loss: 1.9055e-09
Epoch 3563/5000
10/10 - 0s - 9ms/step - loss: 8.5237e-09
Epoch 3564/5000
10/10 - 0s - 9ms/step - loss: 5.6725e-08
Epoch 3565/5000
10/10 - 0s - 9ms/step - loss: 2.2188e-07
Epoch 3566/5000
10/10 - 0s - 9ms/step - loss: 4.3522e-08
Epoch 3567/5000
10/10 - 0s - 8ms/step - loss: 1.6606e-08
Epoch 3568/5000
10/10 - 0s - 8ms/step - loss: 7.9847e-09
Epoch 3569/5000
10/10 - 0s - 10ms/step - loss: 5.9245e-09
Epoch 3570/5000
10/10 - 0s - 8ms/step - loss: 6.4209e-10
Epoch 3571/5000
10/10 - 0s - 10ms/step - loss: 9.4549e-10
Epoch 3572/5000
10/10 - 0s - 10ms/step - loss: 3.5332e-09
Epoch 3573/5000
10/10 - 0s - 8ms/step - loss: 3.5315e-09
Epoch 3574/5000
10/10 - 0s - 9ms/step - loss: 5.5139e-08
Epoch 3575/5000
10/10 - 0s - 9ms/step - loss: 3.8588e-07
Epoch 3576/5000
10/10 - 0s - 9ms/step - loss: 8.6746e-08
Epoch 3577/5000
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Epoch 3578/5000
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Epoch 3579/5000
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Epoch 3580/5000
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Epoch 3581/5000
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Epoch 3582/5000
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Epoch 3583/5000
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Epoch 3584/5000
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Epoch 3585/5000
10/10 - 0s - 9ms/step - loss: 2.4753e-10
Epoch 3586/5000
10/10 - 0s - 9ms/step - loss: 1.6506e-09
Epoch 3587/5000
10/10 - 0s - 8ms/step - loss: 1.3187e-08
Epoch 3588/5000
10/10 - 0s - 10ms/step - loss: 1.1510e-07
Epoch 3589/5000
10/10 - 0s - 8ms/step - loss: 1.4006e-07
Epoch 3590/5000
10/10 - 0s - 8ms/step - loss: 3.4105e-08
Epoch 3591/5000
10/10 - 0s - 10ms/step - loss: 9.8657e-09
Epoch 3592/5000
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Epoch 3593/5000
10/10 - 0s - 10ms/step - loss: 1.3390e-08
Epoch 3594/5000
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Epoch 3595/5000
10/10 - 0s - 10ms/step - loss: 3.8827e-10
Epoch 3596/5000
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Epoch 3597/5000
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Epoch 3598/5000
10/10 - 0s - 9ms/step - loss: 1.5308e-07
Epoch 3599/5000
10/10 - 0s - 9ms/step - loss: 5.3342e-08
Epoch 3600/5000
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Epoch 3601/5000
10/10 - 0s - 10ms/step - loss: 6.6373e-09
Epoch 3602/5000
10/10 - 0s - 8ms/step - loss: 3.2137e-09
Epoch 3603/5000
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Epoch 3604/5000
10/10 - 0s - 9ms/step - loss: 2.4291e-09
Epoch 3605/5000
10/10 - 0s - 9ms/step - loss: 6.6146e-10
Epoch 3606/5000
10/10 - 0s - 9ms/step - loss: 6.3894e-10
Epoch 3607/5000
10/10 - 0s - 9ms/step - loss: 6.1486e-09
Epoch 3608/5000
10/10 - 0s - 8ms/step - loss: 5.0339e-08
Epoch 3609/5000
10/10 - 0s - 9ms/step - loss: 2.5390e-07
Epoch 3610/5000
10/10 - 0s - 9ms/step - loss: 5.8129e-08
Epoch 3611/5000
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Epoch 3612/5000
10/10 - 0s - 8ms/step - loss: 8.8943e-09
Epoch 3613/5000
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Epoch 3614/5000
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Epoch 3615/5000
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Epoch 3616/5000
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Epoch 3617/5000
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Epoch 3618/5000
10/10 - 0s - 9ms/step - loss: 1.3014e-08
Epoch 3619/5000
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Epoch 3620/5000
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Epoch 3621/5000
10/10 - 0s - 8ms/step - loss: 4.6416e-08
Epoch 3622/5000
10/10 - 0s - 9ms/step - loss: 1.2066e-08
Epoch 3623/5000
10/10 - 0s - 9ms/step - loss: 1.0304e-08
Epoch 3624/5000
10/10 - 0s - 7ms/step - loss: 1.8940e-09
Epoch 3625/5000
10/10 - 0s - 9ms/step - loss: 3.8366e-10
Epoch 3626/5000
10/10 - 0s - 9ms/step - loss: 1.4564e-11
Epoch 3627/5000
10/10 - 0s - 7ms/step - loss: 2.3246e-09
Epoch 3628/5000
10/10 - 0s - 9ms/step - loss: 3.1099e-08
Epoch 3629/5000
10/10 - 0s - 10ms/step - loss: 2.0293e-07
Epoch 3630/5000
10/10 - 0s - 9ms/step - loss: 5.5209e-08
Epoch 3631/5000
10/10 - 0s - 8ms/step - loss: 2.9361e-08
Epoch 3632/5000
10/10 - 0s - 9ms/step - loss: 1.5038e-08
Epoch 3633/5000
10/10 - 0s - 9ms/step - loss: 6.1592e-09
Epoch 3634/5000
10/10 - 0s - 9ms/step - loss: 4.8740e-09
Epoch 3635/5000
10/10 - 0s - 12ms/step - loss: 1.0567e-09
Epoch 3636/5000
10/10 - 0s - 14ms/step - loss: 6.1636e-09
Epoch 3637/5000
10/10 - 0s - 9ms/step - loss: 2.8772e-08
Epoch 3638/5000
10/10 - 0s - 10ms/step - loss: 1.9659e-07
Epoch 3639/5000
10/10 - 0s - 9ms/step - loss: 6.3411e-08
Epoch 3640/5000
10/10 - 0s - 10ms/step - loss: 2.8673e-08
Epoch 3641/5000
10/10 - 0s - 12ms/step - loss: 1.1784e-08
Epoch 3642/5000
10/10 - 0s - 20ms/step - loss: 4.5763e-09
Epoch 3643/5000
10/10 - 0s - 9ms/step - loss: 1.9721e-09
Epoch 3644/5000
10/10 - 0s - 9ms/step - loss: 5.2809e-10
Epoch 3645/5000
10/10 - 0s - 9ms/step - loss: 9.0775e-09
Epoch 3646/5000
10/10 - 0s - 19ms/step - loss: 5.9548e-08
Epoch 3647/5000
10/10 - 0s - 18ms/step - loss: 2.0780e-07
Epoch 3648/5000
10/10 - 0s - 20ms/step - loss: 4.0276e-08
Epoch 3649/5000
10/10 - 0s - 15ms/step - loss: 1.8836e-08
Epoch 3650/5000
10/10 - 0s - 9ms/step - loss: 1.4577e-08
Epoch 3651/5000
10/10 - 0s - 9ms/step - loss: 9.7662e-09
Epoch 3652/5000
10/10 - 0s - 8ms/step - loss: 2.0996e-09
Epoch 3653/5000
10/10 - 0s - 8ms/step - loss: 3.5938e-09
Epoch 3654/5000
10/10 - 0s - 7ms/step - loss: 3.7542e-09
Epoch 3655/5000
10/10 - 0s - 8ms/step - loss: 1.5565e-08
Epoch 3656/5000
10/10 - 0s - 18ms/step - loss: 1.9151e-07
Epoch 3657/5000
10/10 - 0s - 9ms/step - loss: 1.3272e-07
Epoch 3658/5000
10/10 - 0s - 9ms/step - loss: 4.9221e-08
Epoch 3659/5000
10/10 - 0s - 9ms/step - loss: 1.7797e-08
Epoch 3660/5000
10/10 - 0s - 9ms/step - loss: 9.2991e-09
Epoch 3661/5000
10/10 - 0s - 9ms/step - loss: 3.2107e-09
Epoch 3662/5000
10/10 - 0s - 17ms/step - loss: 6.3618e-10
Epoch 3663/5000
10/10 - 0s - 9ms/step - loss: 2.0207e-09
Epoch 3664/5000
10/10 - 0s - 8ms/step - loss: 1.9620e-09
Epoch 3665/5000
10/10 - 0s - 9ms/step - loss: 1.0376e-10
Epoch 3666/5000
10/10 - 0s - 9ms/step - loss: 1.9653e-09
Epoch 3667/5000
10/10 - 0s - 8ms/step - loss: 5.7947e-08
Epoch 3668/5000
10/10 - 0s - 9ms/step - loss: 3.7122e-07
Epoch 3669/5000
10/10 - 0s - 9ms/step - loss: 8.8993e-08
Epoch 3670/5000
10/10 - 0s - 9ms/step - loss: 3.9797e-08
Epoch 3671/5000
10/10 - 0s - 10ms/step - loss: 1.3986e-08
Epoch 3672/5000
10/10 - 0s - 9ms/step - loss: 5.5084e-09
Epoch 3673/5000
10/10 - 0s - 9ms/step - loss: 2.0859e-09
Epoch 3674/5000
10/10 - 0s - 9ms/step - loss: 1.9581e-10
Epoch 3675/5000
10/10 - 0s - 9ms/step - loss: 4.1424e-11
Epoch 3676/5000
10/10 - 0s - 9ms/step - loss: 2.1703e-10
Epoch 3677/5000
10/10 - 0s - 9ms/step - loss: 3.3490e-10
Epoch 3678/5000
10/10 - 0s - 9ms/step - loss: 4.3171e-10
Epoch 3679/5000
10/10 - 0s - 9ms/step - loss: 1.2509e-08
Epoch 3680/5000
10/10 - 0s - 9ms/step - loss: 6.6279e-08
Epoch 3681/5000
10/10 - 0s - 7ms/step - loss: 9.2485e-08
Epoch 3682/5000
10/10 - 0s - 9ms/step - loss: 8.4181e-09
Epoch 3683/5000
10/10 - 0s - 9ms/step - loss: 2.6161e-08
Epoch 3684/5000
10/10 - 0s - 10ms/step - loss: 6.2429e-09
Epoch 3685/5000
10/10 - 0s - 8ms/step - loss: 7.6556e-09
Epoch 3686/5000
10/10 - 0s - 10ms/step - loss: 5.6063e-08
Epoch 3687/5000
10/10 - 0s - 9ms/step - loss: 1.5576e-07
Epoch 3688/5000
10/10 - 0s - 9ms/step - loss: 2.3612e-08
Epoch 3689/5000
10/10 - 0s - 8ms/step - loss: 2.4437e-08
Epoch 3690/5000
10/10 - 0s - 8ms/step - loss: 9.7161e-09
Epoch 3691/5000
10/10 - 0s - 8ms/step - loss: 5.4080e-09
Epoch 3692/5000
10/10 - 0s - 11ms/step - loss: 8.4763e-10
Epoch 3693/5000
10/10 - 0s - 12ms/step - loss: 6.8082e-09
Epoch 3694/5000
10/10 - 0s - 11ms/step - loss: 7.5830e-08
Epoch 3695/5000
10/10 - 0s - 11ms/step - loss: 2.4107e-07
Epoch 3696/5000
10/10 - 0s - 18ms/step - loss: 5.1863e-08
Epoch 3697/5000
10/10 - 0s - 8ms/step - loss: 1.4459e-08
Epoch 3698/5000
10/10 - 0s - 9ms/step - loss: 3.5861e-09
Epoch 3699/5000
10/10 - 0s - 11ms/step - loss: 1.5236e-09
Epoch 3700/5000
10/10 - 0s - 9ms/step - loss: 1.3674e-09
Epoch 3701/5000
10/10 - 0s - 9ms/step - loss: 1.4847e-10
Epoch 3702/5000
10/10 - 0s - 7ms/step - loss: 2.7877e-10
Epoch 3703/5000
10/10 - 0s - 10ms/step - loss: 2.0870e-09
Epoch 3704/5000
10/10 - 0s - 7ms/step - loss: 6.8923e-09
Epoch 3705/5000
10/10 - 0s - 9ms/step - loss: 2.0622e-07
Epoch 3706/5000
10/10 - 0s - 7ms/step - loss: 2.7854e-07
Epoch 3707/5000
10/10 - 0s - 10ms/step - loss: 8.9290e-08
Epoch 3708/5000
10/10 - 0s - 8ms/step - loss: 2.1712e-08
Epoch 3709/5000
10/10 - 0s - 10ms/step - loss: 9.1762e-09
Epoch 3710/5000
10/10 - 0s - 9ms/step - loss: 4.5891e-09
Epoch 3711/5000
10/10 - 0s - 7ms/step - loss: 1.1046e-09
Epoch 3712/5000
10/10 - 0s - 10ms/step - loss: 3.1465e-10
Epoch 3713/5000
10/10 - 0s - 8ms/step - loss: 3.0926e-10
Epoch 3714/5000
10/10 - 0s - 9ms/step - loss: 1.7440e-10
Epoch 3715/5000
10/10 - 0s - 9ms/step - loss: 9.1362e-12
Epoch 3716/5000
10/10 - 0s - 9ms/step - loss: 1.3438e-11
Epoch 3717/5000
10/10 - 0s - 9ms/step - loss: 5.7573e-10
Epoch 3718/5000
10/10 - 0s - 8ms/step - loss: 4.2999e-09
Epoch 3719/5000
10/10 - 0s - 8ms/step - loss: 2.5945e-08
Epoch 3720/5000
10/10 - 0s - 8ms/step - loss: 1.9262e-07
Epoch 3721/5000
10/10 - 0s - 8ms/step - loss: 1.0114e-07
Epoch 3722/5000
10/10 - 0s - 8ms/step - loss: 4.0879e-08
Epoch 3723/5000
10/10 - 0s - 10ms/step - loss: 1.7392e-08
Epoch 3724/5000
10/10 - 0s - 10ms/step - loss: 1.1907e-08
Epoch 3725/5000
10/10 - 0s - 8ms/step - loss: 2.3594e-09
Epoch 3726/5000
10/10 - 0s - 9ms/step - loss: 4.9200e-09
Epoch 3727/5000
10/10 - 0s - 8ms/step - loss: 1.1921e-09
Epoch 3728/5000
10/10 - 0s - 10ms/step - loss: 5.6054e-09
Epoch 3729/5000
10/10 - 0s - 9ms/step - loss: 6.9056e-09
Epoch 3730/5000
10/10 - 0s - 8ms/step - loss: 6.3766e-08
Epoch 3731/5000
10/10 - 0s - 8ms/step - loss: 2.7076e-07
Epoch 3732/5000
10/10 - 0s - 9ms/step - loss: 5.7762e-08
Epoch 3733/5000
10/10 - 0s - 17ms/step - loss: 2.3285e-08
Epoch 3734/5000
10/10 - 0s - 17ms/step - loss: 1.1470e-08
Epoch 3735/5000
10/10 - 0s - 9ms/step - loss: 4.3029e-09
Epoch 3736/5000
10/10 - 0s - 7ms/step - loss: 1.2472e-09
Epoch 3737/5000
10/10 - 0s - 9ms/step - loss: 3.6515e-10
Epoch 3738/5000
10/10 - 0s - 7ms/step - loss: 3.7072e-10
Epoch 3739/5000
10/10 - 0s - 9ms/step - loss: 2.3622e-09
Epoch 3740/5000
10/10 - 0s - 9ms/step - loss: 2.6634e-09
Epoch 3741/5000
10/10 - 0s - 9ms/step - loss: 2.9155e-08
Epoch 3742/5000
10/10 - 0s - 8ms/step - loss: 2.8452e-07
Epoch 3743/5000
10/10 - 0s - 8ms/step - loss: 9.2152e-08
Epoch 3744/5000
10/10 - 0s - 8ms/step - loss: 3.0381e-08
Epoch 3745/5000
10/10 - 0s - 8ms/step - loss: 1.2206e-08
Epoch 3746/5000
10/10 - 0s - 9ms/step - loss: 6.2761e-09
Epoch 3747/5000
10/10 - 0s - 9ms/step - loss: 3.1544e-09
Epoch 3748/5000
10/10 - 0s - 10ms/step - loss: 2.2216e-09
Epoch 3749/5000
10/10 - 0s - 18ms/step - loss: 1.2007e-09
Epoch 3750/5000
10/10 - 0s - 16ms/step - loss: 2.3569e-10
Epoch 3751/5000
10/10 - 0s - 8ms/step - loss: 5.5762e-11
Epoch 3752/5000
10/10 - 0s - 16ms/step - loss: 1.2313e-09
Epoch 3753/5000
10/10 - 0s - 8ms/step - loss: 4.3697e-08
Epoch 3754/5000
10/10 - 0s - 8ms/step - loss: 3.0629e-07
Epoch 3755/5000
10/10 - 0s - 10ms/step - loss: 7.4568e-08
Epoch 3756/5000
10/10 - 0s - 9ms/step - loss: 2.7272e-08
Epoch 3757/5000
10/10 - 0s - 8ms/step - loss: 1.2384e-08
Epoch 3758/5000
10/10 - 0s - 8ms/step - loss: 5.0586e-09
Epoch 3759/5000
10/10 - 0s - 10ms/step - loss: 6.4814e-10
Epoch 3760/5000
10/10 - 0s - 10ms/step - loss: 3.4050e-10
Epoch 3761/5000
10/10 - 0s - 9ms/step - loss: 3.4056e-10
Epoch 3762/5000
10/10 - 0s - 9ms/step - loss: 6.6036e-11
Epoch 3763/5000
10/10 - 0s - 9ms/step - loss: 4.3830e-09
Epoch 3764/5000
10/10 - 0s - 10ms/step - loss: 1.7339e-08
Epoch 3765/5000
10/10 - 0s - 10ms/step - loss: 9.0502e-08
Epoch 3766/5000
10/10 - 0s - 9ms/step - loss: 1.3292e-07
Epoch 3767/5000
10/10 - 0s - 8ms/step - loss: 3.4451e-08
Epoch 3768/5000
10/10 - 0s - 10ms/step - loss: 1.2782e-08
Epoch 3769/5000
10/10 - 0s - 9ms/step - loss: 1.3031e-08
Epoch 3770/5000
10/10 - 0s - 9ms/step - loss: 2.0786e-09
Epoch 3771/5000
10/10 - 0s - 9ms/step - loss: 9.9648e-09
Epoch 3772/5000
10/10 - 0s - 8ms/step - loss: 4.1156e-08
Epoch 3773/5000
10/10 - 0s - 9ms/step - loss: 8.8194e-08
Epoch 3774/5000
10/10 - 0s - 9ms/step - loss: 3.7465e-08
Epoch 3775/5000
10/10 - 0s - 9ms/step - loss: 1.5580e-09
Epoch 3776/5000
10/10 - 0s - 17ms/step - loss: 8.8274e-09
Epoch 3777/5000
10/10 - 0s - 9ms/step - loss: 3.3218e-08
Epoch 3778/5000
10/10 - 0s - 8ms/step - loss: 1.6859e-07
Epoch 3779/5000
10/10 - 0s - 9ms/step - loss: 5.6922e-08
Epoch 3780/5000
10/10 - 0s - 9ms/step - loss: 3.5773e-08
Epoch 3781/5000
10/10 - 0s - 8ms/step - loss: 9.4297e-09
Epoch 3782/5000
10/10 - 0s - 9ms/step - loss: 1.2215e-09
Epoch 3783/5000
10/10 - 0s - 8ms/step - loss: 2.2949e-09
Epoch 3784/5000
10/10 - 0s - 8ms/step - loss: 1.0167e-09
Epoch 3785/5000
10/10 - 0s - 9ms/step - loss: 1.5600e-09
Epoch 3786/5000
10/10 - 0s - 8ms/step - loss: 6.9470e-09
Epoch 3787/5000
10/10 - 0s - 9ms/step - loss: 1.6683e-07
Epoch 3788/5000
10/10 - 0s - 8ms/step - loss: 2.7490e-07
Epoch 3789/5000
10/10 - 0s - 10ms/step - loss: 8.0756e-08
Epoch 3790/5000
10/10 - 0s - 9ms/step - loss: 2.4366e-08
Epoch 3791/5000
10/10 - 0s - 9ms/step - loss: 7.2084e-09
Epoch 3792/5000
10/10 - 0s - 12ms/step - loss: 4.0997e-09
Epoch 3793/5000
10/10 - 0s - 14ms/step - loss: 1.3195e-09
Epoch 3794/5000
10/10 - 0s - 12ms/step - loss: 8.0756e-10
Epoch 3795/5000
10/10 - 0s - 9ms/step - loss: 2.1317e-11
Epoch 3796/5000
10/10 - 0s - 10ms/step - loss: 6.5584e-10
Epoch 3797/5000
10/10 - 0s - 9ms/step - loss: 7.2582e-10
Epoch 3798/5000
10/10 - 0s - 8ms/step - loss: 1.2268e-09
Epoch 3799/5000
10/10 - 0s - 8ms/step - loss: 1.1261e-08
Epoch 3800/5000
10/10 - 0s - 9ms/step - loss: 7.3826e-08
Epoch 3801/5000
10/10 - 0s - 8ms/step - loss: 1.5916e-07
Epoch 3802/5000
10/10 - 0s - 9ms/step - loss: 2.8868e-08
Epoch 3803/5000
10/10 - 0s - 9ms/step - loss: 9.0863e-09
Epoch 3804/5000
10/10 - 0s - 8ms/step - loss: 6.5203e-09
Epoch 3805/5000
10/10 - 0s - 8ms/step - loss: 1.1669e-10
Epoch 3806/5000
10/10 - 0s - 10ms/step - loss: 7.3588e-11
Epoch 3807/5000
10/10 - 0s - 9ms/step - loss: 7.9472e-11
Epoch 3808/5000
10/10 - 0s - 18ms/step - loss: 9.3190e-10
Epoch 3809/5000
10/10 - 0s - 9ms/step - loss: 4.3646e-08
Epoch 3810/5000
10/10 - 0s - 8ms/step - loss: 4.8167e-07
Epoch 3811/5000
10/10 - 0s - 9ms/step - loss: 1.3151e-07
Epoch 3812/5000
10/10 - 0s - 9ms/step - loss: 6.8607e-08
Epoch 3813/5000
10/10 - 0s - 9ms/step - loss: 1.3808e-08
Epoch 3814/5000
10/10 - 0s - 8ms/step - loss: 7.9478e-09
Epoch 3815/5000
10/10 - 0s - 10ms/step - loss: 1.2187e-09
Epoch 3816/5000
10/10 - 0s - 9ms/step - loss: 2.5790e-10
Epoch 3817/5000
10/10 - 0s - 10ms/step - loss: 2.5327e-10
Epoch 3818/5000
10/10 - 0s - 7ms/step - loss: 2.3535e-10
Epoch 3819/5000
10/10 - 0s - 8ms/step - loss: 3.0990e-10
Epoch 3820/5000
10/10 - 0s - 9ms/step - loss: 6.3168e-11
Epoch 3821/5000
10/10 - 0s - 8ms/step - loss: 7.6309e-10
Epoch 3822/5000
10/10 - 0s - 10ms/step - loss: 6.6916e-11
Epoch 3823/5000
10/10 - 0s - 9ms/step - loss: 2.3687e-10
Epoch 3824/5000
10/10 - 0s - 9ms/step - loss: 3.9027e-11
Epoch 3825/5000
10/10 - 0s - 8ms/step - loss: 2.5107e-10
Epoch 3826/5000
10/10 - 0s - 9ms/step - loss: 9.0178e-09
Epoch 3827/5000
10/10 - 0s - 8ms/step - loss: 9.6142e-08
Epoch 3828/5000
10/10 - 0s - 10ms/step - loss: 2.2425e-07
Epoch 3829/5000
10/10 - 0s - 10ms/step - loss: 6.0830e-08
Epoch 3830/5000
10/10 - 0s - 9ms/step - loss: 2.3564e-08
Epoch 3831/5000
10/10 - 0s - 8ms/step - loss: 8.5719e-09
Epoch 3832/5000
10/10 - 0s - 8ms/step - loss: 6.3506e-09
Epoch 3833/5000
10/10 - 0s - 9ms/step - loss: 3.3151e-09
Epoch 3834/5000
10/10 - 0s - 8ms/step - loss: 1.7042e-09
Epoch 3835/5000
10/10 - 0s - 10ms/step - loss: 2.6967e-09
Epoch 3836/5000
10/10 - 0s - 9ms/step - loss: 6.2951e-11
Epoch 3837/5000
10/10 - 0s - 8ms/step - loss: 9.6468e-10
Epoch 3838/5000
10/10 - 0s - 8ms/step - loss: 3.4017e-08
Epoch 3839/5000
10/10 - 0s - 8ms/step - loss: 3.2087e-07
Epoch 3840/5000
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Epoch 3841/5000
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Epoch 3842/5000
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Epoch 3843/5000
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Epoch 3844/5000
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Epoch 3845/5000
10/10 - 0s - 10ms/step - loss: 4.8015e-10
Epoch 3846/5000
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Epoch 3847/5000
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Epoch 3848/5000
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Epoch 3849/5000
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Epoch 3850/5000
10/10 - 0s - 9ms/step - loss: 7.0019e-09
Epoch 3851/5000
10/10 - 0s - 9ms/step - loss: 8.6230e-08
Epoch 3852/5000
10/10 - 0s - 8ms/step - loss: 2.6768e-07
Epoch 3853/5000
10/10 - 0s - 10ms/step - loss: 5.3920e-08
Epoch 3854/5000
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Epoch 3855/5000
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Epoch 3856/5000
10/10 - 0s - 9ms/step - loss: 2.8658e-09
Epoch 3857/5000
10/10 - 0s - 10ms/step - loss: 8.7660e-10
Epoch 3858/5000
10/10 - 0s - 8ms/step - loss: 9.4437e-10
Epoch 3859/5000
10/10 - 0s - 7ms/step - loss: 4.7133e-09
Epoch 3860/5000
10/10 - 0s - 10ms/step - loss: 6.5110e-10
Epoch 3861/5000
10/10 - 0s - 9ms/step - loss: 1.8512e-09
Epoch 3862/5000
10/10 - 0s - 9ms/step - loss: 3.8209e-08
Epoch 3863/5000
10/10 - 0s - 9ms/step - loss: 2.6709e-07
Epoch 3864/5000
10/10 - 0s - 9ms/step - loss: 7.3504e-08
Epoch 3865/5000
10/10 - 0s - 7ms/step - loss: 2.9035e-08
Epoch 3866/5000
10/10 - 0s - 9ms/step - loss: 9.5525e-09
Epoch 3867/5000
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Epoch 3868/5000
10/10 - 0s - 9ms/step - loss: 5.8132e-10
Epoch 3869/5000
10/10 - 0s - 9ms/step - loss: 2.6743e-10
Epoch 3870/5000
10/10 - 0s - 9ms/step - loss: 3.1089e-11
Epoch 3871/5000
10/10 - 0s - 10ms/step - loss: 4.9025e-10
Epoch 3872/5000
10/10 - 0s - 9ms/step - loss: 1.7387e-09
Epoch 3873/5000
10/10 - 0s - 7ms/step - loss: 1.9198e-08
Epoch 3874/5000
10/10 - 0s - 8ms/step - loss: 2.6258e-07
Epoch 3875/5000
10/10 - 0s - 7ms/step - loss: 1.3044e-07
Epoch 3876/5000
10/10 - 0s - 9ms/step - loss: 3.7522e-08
Epoch 3877/5000
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Epoch 3878/5000
10/10 - 0s - 8ms/step - loss: 5.5490e-09
Epoch 3879/5000
10/10 - 0s - 9ms/step - loss: 2.0959e-09
Epoch 3880/5000
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Epoch 3881/5000
10/10 - 0s - 8ms/step - loss: 1.6822e-09
Epoch 3882/5000
10/10 - 0s - 9ms/step - loss: 1.7973e-09
Epoch 3883/5000
10/10 - 0s - 8ms/step - loss: 4.0102e-10
Epoch 3884/5000
10/10 - 0s - 9ms/step - loss: 4.3279e-09
Epoch 3885/5000
10/10 - 0s - 10ms/step - loss: 5.5834e-08
Epoch 3886/5000
10/10 - 0s - 8ms/step - loss: 2.0587e-07
Epoch 3887/5000
10/10 - 0s - 9ms/step - loss: 3.7499e-08
Epoch 3888/5000
10/10 - 0s - 18ms/step - loss: 1.6548e-08
Epoch 3889/5000
10/10 - 0s - 9ms/step - loss: 9.9433e-09
Epoch 3890/5000
10/10 - 0s - 9ms/step - loss: 3.7136e-09
Epoch 3891/5000
10/10 - 0s - 9ms/step - loss: 1.8923e-10
Epoch 3892/5000
10/10 - 0s - 10ms/step - loss: 8.2638e-10
Epoch 3893/5000
10/10 - 0s - 8ms/step - loss: 8.2225e-09
Epoch 3894/5000
10/10 - 0s - 8ms/step - loss: 5.3633e-08
Epoch 3895/5000
10/10 - 0s - 9ms/step - loss: 2.0559e-07
Epoch 3896/5000
10/10 - 0s - 10ms/step - loss: 4.0620e-08
Epoch 3897/5000
10/10 - 0s - 9ms/step - loss: 1.9213e-08
Epoch 3898/5000
10/10 - 0s - 9ms/step - loss: 1.1342e-08
Epoch 3899/5000
10/10 - 0s - 8ms/step - loss: 6.9810e-09
Epoch 3900/5000
10/10 - 0s - 10ms/step - loss: 2.5388e-09
Epoch 3901/5000
10/10 - 0s - 8ms/step - loss: 4.6313e-09
Epoch 3902/5000
10/10 - 0s - 9ms/step - loss: 2.9058e-09
Epoch 3903/5000
10/10 - 0s - 8ms/step - loss: 8.3410e-09
Epoch 3904/5000
10/10 - 0s - 10ms/step - loss: 8.2152e-08
Epoch 3905/5000
10/10 - 0s - 23ms/step - loss: 2.8770e-07
Epoch 3906/5000
10/10 - 0s - 10ms/step - loss: 6.7492e-08
Epoch 3907/5000
10/10 - 0s - 9ms/step - loss: 2.2793e-08
Epoch 3908/5000
10/10 - 0s - 7ms/step - loss: 9.7526e-09
Epoch 3909/5000
10/10 - 0s - 8ms/step - loss: 3.4196e-09
Epoch 3910/5000
10/10 - 0s - 9ms/step - loss: 1.1546e-09
Epoch 3911/5000
10/10 - 0s - 9ms/step - loss: 2.1923e-09
Epoch 3912/5000
10/10 - 0s - 18ms/step - loss: 1.6230e-09
Epoch 3913/5000
10/10 - 0s - 8ms/step - loss: 3.6149e-11
Epoch 3914/5000
10/10 - 0s - 9ms/step - loss: 9.1729e-10
Epoch 3915/5000
10/10 - 0s - 9ms/step - loss: 2.1324e-09
Epoch 3916/5000
10/10 - 0s - 8ms/step - loss: 4.8117e-08
Epoch 3917/5000
10/10 - 0s - 7ms/step - loss: 2.8194e-07
Epoch 3918/5000
10/10 - 0s - 8ms/step - loss: 6.1789e-08
Epoch 3919/5000
10/10 - 0s - 9ms/step - loss: 2.0694e-08
Epoch 3920/5000
10/10 - 0s - 10ms/step - loss: 6.6332e-09
Epoch 3921/5000
10/10 - 0s - 9ms/step - loss: 1.8590e-09
Epoch 3922/5000
10/10 - 0s - 7ms/step - loss: 8.0838e-10
Epoch 3923/5000
10/10 - 0s - 9ms/step - loss: 1.0866e-10
Epoch 3924/5000
10/10 - 0s - 7ms/step - loss: 2.0544e-10
Epoch 3925/5000
10/10 - 0s - 10ms/step - loss: 4.3131e-09
Epoch 3926/5000
10/10 - 0s - 8ms/step - loss: 1.8037e-08
Epoch 3927/5000
10/10 - 0s - 8ms/step - loss: 1.0733e-07
Epoch 3928/5000
10/10 - 0s - 9ms/step - loss: 1.1230e-07
Epoch 3929/5000
10/10 - 0s - 8ms/step - loss: 3.5213e-08
Epoch 3930/5000
10/10 - 0s - 17ms/step - loss: 6.0972e-09
Epoch 3931/5000
10/10 - 0s - 9ms/step - loss: 6.4356e-09
Epoch 3932/5000
10/10 - 0s - 8ms/step - loss: 1.3640e-09
Epoch 3933/5000
10/10 - 0s - 8ms/step - loss: 1.1178e-08
Epoch 3934/5000
10/10 - 0s - 9ms/step - loss: 5.6914e-08
Epoch 3935/5000
10/10 - 0s - 9ms/step - loss: 1.0374e-07
Epoch 3936/5000
10/10 - 0s - 10ms/step - loss: 1.1426e-08
Epoch 3937/5000
10/10 - 0s - 9ms/step - loss: 1.9867e-08
Epoch 3938/5000
10/10 - 0s - 8ms/step - loss: 5.7305e-09
Epoch 3939/5000
10/10 - 0s - 9ms/step - loss: 1.6008e-11
Epoch 3940/5000
10/10 - 0s - 9ms/step - loss: 1.2016e-10
Epoch 3941/5000
10/10 - 0s - 8ms/step - loss: 1.3765e-08
Epoch 3942/5000
10/10 - 0s - 8ms/step - loss: 4.1175e-07
Epoch 3943/5000
10/10 - 0s - 9ms/step - loss: 1.7856e-07
Epoch 3944/5000
10/10 - 0s - 9ms/step - loss: 5.5769e-08
Epoch 3945/5000
10/10 - 0s - 8ms/step - loss: 3.0135e-08
Epoch 3946/5000
10/10 - 0s - 8ms/step - loss: 6.0994e-09
Epoch 3947/5000
10/10 - 0s - 8ms/step - loss: 3.5733e-09
Epoch 3948/5000
10/10 - 0s - 9ms/step - loss: 1.4349e-09
Epoch 3949/5000
10/10 - 0s - 9ms/step - loss: 3.9533e-10
Epoch 3950/5000
10/10 - 0s - 10ms/step - loss: 7.5128e-10
Epoch 3951/5000
10/10 - 0s - 8ms/step - loss: 4.4299e-10
Epoch 3952/5000
10/10 - 0s - 9ms/step - loss: 1.3629e-10
Epoch 3953/5000
10/10 - 0s - 8ms/step - loss: 2.8627e-11
Epoch 3954/5000
10/10 - 0s - 9ms/step - loss: 1.6320e-10
Epoch 3955/5000
10/10 - 0s - 9ms/step - loss: 3.6174e-10
Epoch 3956/5000
10/10 - 0s - 10ms/step - loss: 4.3611e-10
Epoch 3957/5000
10/10 - 0s - 10ms/step - loss: 4.3526e-09
Epoch 3958/5000
10/10 - 0s - 9ms/step - loss: 3.8262e-08
Epoch 3959/5000
10/10 - 0s - 9ms/step - loss: 2.4216e-07
Epoch 3960/5000
10/10 - 0s - 21ms/step - loss: 6.3678e-08
Epoch 3961/5000
10/10 - 0s - 10ms/step - loss: 2.5933e-08
Epoch 3962/5000
10/10 - 0s - 8ms/step - loss: 9.3338e-09
Epoch 3963/5000
10/10 - 0s - 10ms/step - loss: 3.8248e-09
Epoch 3964/5000
10/10 - 0s - 9ms/step - loss: 2.8474e-09
Epoch 3965/5000
10/10 - 0s - 9ms/step - loss: 4.3030e-10
Epoch 3966/5000
10/10 - 0s - 8ms/step - loss: 6.2855e-09
Epoch 3967/5000
10/10 - 0s - 8ms/step - loss: 1.1201e-08
Epoch 3968/5000
10/10 - 0s - 10ms/step - loss: 2.9516e-08
Epoch 3969/5000
10/10 - 0s - 9ms/step - loss: 1.1085e-07
Epoch 3970/5000
10/10 - 0s - 12ms/step - loss: 8.9873e-08
Epoch 3971/5000
10/10 - 0s - 15ms/step - loss: 2.2007e-08
Epoch 3972/5000
10/10 - 0s - 22ms/step - loss: 6.8144e-09
Epoch 3973/5000
10/10 - 0s - 16ms/step - loss: 4.3627e-09
Epoch 3974/5000
10/10 - 0s - 9ms/step - loss: 1.9784e-09
Epoch 3975/5000
10/10 - 0s - 9ms/step - loss: 3.9490e-10
Epoch 3976/5000
10/10 - 0s - 9ms/step - loss: 1.0385e-09
Epoch 3977/5000
10/10 - 0s - 9ms/step - loss: 3.6593e-08
Epoch 3978/5000
10/10 - 0s - 9ms/step - loss: 4.5416e-07
Epoch 3979/5000
10/10 - 0s - 10ms/step - loss: 1.0558e-07
Epoch 3980/5000
10/10 - 0s - 15ms/step - loss: 6.1113e-08
Epoch 3981/5000
10/10 - 0s - 25ms/step - loss: 2.1333e-08
Epoch 3982/5000
10/10 - 0s - 12ms/step - loss: 6.8509e-09
Epoch 3983/5000
10/10 - 0s - 16ms/step - loss: 2.4137e-09
Epoch 3984/5000
10/10 - 0s - 9ms/step - loss: 1.0109e-09
Epoch 3985/5000
10/10 - 0s - 16ms/step - loss: 5.1486e-10
Epoch 3986/5000
10/10 - 0s - 9ms/step - loss: 2.0424e-10
Epoch 3987/5000
10/10 - 0s - 10ms/step - loss: 7.2547e-11
Epoch 3988/5000
10/10 - 0s - 8ms/step - loss: 5.9534e-10
Epoch 3989/5000
10/10 - 0s - 9ms/step - loss: 4.6305e-10
Epoch 3990/5000
10/10 - 0s - 9ms/step - loss: 1.9075e-09
Epoch 3991/5000
10/10 - 0s - 8ms/step - loss: 2.5062e-09
Epoch 3992/5000
10/10 - 0s - 9ms/step - loss: 1.6655e-09
Epoch 3993/5000
10/10 - 0s - 9ms/step - loss: 1.6520e-08
Epoch 3994/5000
10/10 - 0s - 10ms/step - loss: 1.9106e-07
Epoch 3995/5000
10/10 - 0s - 9ms/step - loss: 1.0136e-07
Epoch 3996/5000
10/10 - 0s - 9ms/step - loss: 4.1221e-08
Epoch 3997/5000
10/10 - 0s - 9ms/step - loss: 1.9736e-08
Epoch 3998/5000
10/10 - 0s - 8ms/step - loss: 1.1321e-08
Epoch 3999/5000
10/10 - 0s - 9ms/step - loss: 3.1992e-09
Epoch 4000/5000
10/10 - 0s - 9ms/step - loss: 7.7151e-10
Epoch 4001/5000
10/10 - 0s - 10ms/step - loss: 1.3486e-09
Epoch 4002/5000
10/10 - 0s - 8ms/step - loss: 1.2947e-11
Epoch 4003/5000
10/10 - 0s - 9ms/step - loss: 2.4149e-10
Epoch 4004/5000
10/10 - 0s - 9ms/step - loss: 9.3338e-09
Epoch 4005/5000
10/10 - 0s - 9ms/step - loss: 2.5663e-07
Epoch 4006/5000
10/10 - 0s - 9ms/step - loss: 2.2692e-07
Epoch 4007/5000
10/10 - 0s - 9ms/step - loss: 6.0374e-08
Epoch 4008/5000
10/10 - 0s - 9ms/step - loss: 1.6905e-08
Epoch 4009/5000
10/10 - 0s - 9ms/step - loss: 7.6424e-09
Epoch 4010/5000
10/10 - 0s - 8ms/step - loss: 3.1286e-09
Epoch 4011/5000
10/10 - 0s - 9ms/step - loss: 1.3863e-09
Epoch 4012/5000
10/10 - 0s - 9ms/step - loss: 7.6666e-10
Epoch 4013/5000
10/10 - 0s - 18ms/step - loss: 3.7121e-10
Epoch 4014/5000
10/10 - 0s - 9ms/step - loss: 4.7690e-11
Epoch 4015/5000
10/10 - 0s - 8ms/step - loss: 3.1116e-10
Epoch 4016/5000
10/10 - 0s - 9ms/step - loss: 2.9142e-09
Epoch 4017/5000
10/10 - 0s - 8ms/step - loss: 8.9613e-09
Epoch 4018/5000
10/10 - 0s - 8ms/step - loss: 2.8864e-08
Epoch 4019/5000
10/10 - 0s - 8ms/step - loss: 7.8872e-08
Epoch 4020/5000
10/10 - 0s - 9ms/step - loss: 8.0260e-08
Epoch 4021/5000
10/10 - 0s - 9ms/step - loss: 1.0152e-08
Epoch 4022/5000
10/10 - 0s - 9ms/step - loss: 1.8067e-08
Epoch 4023/5000
10/10 - 0s - 9ms/step - loss: 1.0131e-08
Epoch 4024/5000
10/10 - 0s - 9ms/step - loss: 5.5001e-09
Epoch 4025/5000
10/10 - 0s - 8ms/step - loss: 2.5008e-08
Epoch 4026/5000
10/10 - 0s - 9ms/step - loss: 1.6790e-07
Epoch 4027/5000
10/10 - 0s - 9ms/step - loss: 9.7547e-08
Epoch 4028/5000
10/10 - 0s - 8ms/step - loss: 3.5107e-08
Epoch 4029/5000
10/10 - 0s - 20ms/step - loss: 1.6213e-08
Epoch 4030/5000
10/10 - 0s - 15ms/step - loss: 3.6215e-09
Epoch 4031/5000
10/10 - 0s - 9ms/step - loss: 8.1122e-10
Epoch 4032/5000
10/10 - 0s - 7ms/step - loss: 6.2540e-09
Epoch 4033/5000
10/10 - 0s - 9ms/step - loss: 5.3007e-09
Epoch 4034/5000
10/10 - 0s - 9ms/step - loss: 5.4537e-09
Epoch 4035/5000
10/10 - 0s - 10ms/step - loss: 1.6214e-08
Epoch 4036/5000
10/10 - 0s - 8ms/step - loss: 2.7711e-07
Epoch 4037/5000
10/10 - 0s - 9ms/step - loss: 1.5614e-07
Epoch 4038/5000
10/10 - 0s - 9ms/step - loss: 4.8229e-08
Epoch 4039/5000
10/10 - 0s - 9ms/step - loss: 1.3349e-08
Epoch 4040/5000
10/10 - 0s - 8ms/step - loss: 6.9510e-09
Epoch 4041/5000
10/10 - 0s - 8ms/step - loss: 2.1154e-09
Epoch 4042/5000
10/10 - 0s - 10ms/step - loss: 2.2191e-09
Epoch 4043/5000
10/10 - 0s - 9ms/step - loss: 7.6234e-10
Epoch 4044/5000
10/10 - 0s - 8ms/step - loss: 6.7706e-10
Epoch 4045/5000
10/10 - 0s - 9ms/step - loss: 2.3140e-09
Epoch 4046/5000
10/10 - 0s - 9ms/step - loss: 1.1004e-09
Epoch 4047/5000
10/10 - 0s - 7ms/step - loss: 5.6853e-09
Epoch 4048/5000
10/10 - 0s - 9ms/step - loss: 3.8173e-08
Epoch 4049/5000
10/10 - 0s - 9ms/step - loss: 1.4401e-07
Epoch 4050/5000
10/10 - 0s - 8ms/step - loss: 4.0045e-08
Epoch 4051/5000
10/10 - 0s - 10ms/step - loss: 2.0489e-08
Epoch 4052/5000
10/10 - 0s - 10ms/step - loss: 4.6594e-09
Epoch 4053/5000
10/10 - 0s - 9ms/step - loss: 4.6989e-09
Epoch 4054/5000
10/10 - 0s - 10ms/step - loss: 3.6828e-10
Epoch 4055/5000
10/10 - 0s - 8ms/step - loss: 1.8620e-10
Epoch 4056/5000
10/10 - 0s - 9ms/step - loss: 5.5211e-09
Epoch 4057/5000
10/10 - 0s - 7ms/step - loss: 1.6098e-07
Epoch 4058/5000
10/10 - 0s - 8ms/step - loss: 3.1334e-07
Epoch 4059/5000
10/10 - 0s - 8ms/step - loss: 1.0334e-07
Epoch 4060/5000
10/10 - 0s - 10ms/step - loss: 2.5144e-08
Epoch 4061/5000
10/10 - 0s - 8ms/step - loss: 1.0036e-08
Epoch 4062/5000
10/10 - 0s - 8ms/step - loss: 4.5955e-09
Epoch 4063/5000
10/10 - 0s - 9ms/step - loss: 8.5583e-10
Epoch 4064/5000
10/10 - 0s - 8ms/step - loss: 2.4495e-10
Epoch 4065/5000
10/10 - 0s - 8ms/step - loss: 2.4797e-11
Epoch 4066/5000
10/10 - 0s - 8ms/step - loss: 6.5748e-10
Epoch 4067/5000
10/10 - 0s - 8ms/step - loss: 3.7197e-10
Epoch 4068/5000
10/10 - 0s - 8ms/step - loss: 6.5533e-10
Epoch 4069/5000
10/10 - 0s - 8ms/step - loss: 5.5403e-10
Epoch 4070/5000
10/10 - 0s - 8ms/step - loss: 3.3569e-10
Epoch 4071/5000
10/10 - 0s - 9ms/step - loss: 4.7399e-09
Epoch 4072/5000
10/10 - 0s - 9ms/step - loss: 5.9581e-08
Epoch 4073/5000
10/10 - 0s - 9ms/step - loss: 2.6490e-07
Epoch 4074/5000
10/10 - 0s - 8ms/step - loss: 5.2783e-08
Epoch 4075/5000
10/10 - 0s - 9ms/step - loss: 1.9034e-08
Epoch 4076/5000
10/10 - 0s - 9ms/step - loss: 9.3352e-09
Epoch 4077/5000
10/10 - 0s - 9ms/step - loss: 5.0984e-09
Epoch 4078/5000
10/10 - 0s - 9ms/step - loss: 2.5702e-09
Epoch 4079/5000
10/10 - 0s - 9ms/step - loss: 3.6443e-09
Epoch 4080/5000
10/10 - 0s - 8ms/step - loss: 5.4740e-10
Epoch 4081/5000
10/10 - 0s - 18ms/step - loss: 5.7759e-09
Epoch 4082/5000
10/10 - 0s - 9ms/step - loss: 1.8448e-08
Epoch 4083/5000
10/10 - 0s - 10ms/step - loss: 8.0287e-08
Epoch 4084/5000
10/10 - 0s - 8ms/step - loss: 1.0222e-07
Epoch 4085/5000
10/10 - 0s - 11ms/step - loss: 2.5319e-08
Epoch 4086/5000
10/10 - 0s - 19ms/step - loss: 2.4558e-08
Epoch 4087/5000
10/10 - 0s - 8ms/step - loss: 8.9976e-09
Epoch 4088/5000
10/10 - 0s - 10ms/step - loss: 1.7801e-08
Epoch 4089/5000
10/10 - 0s - 15ms/step - loss: 6.7670e-09
Epoch 4090/5000
10/10 - 0s - 8ms/step - loss: 2.1883e-09
Epoch 4091/5000
10/10 - 0s - 10ms/step - loss: 4.4359e-10
Epoch 4092/5000
10/10 - 0s - 9ms/step - loss: 2.2332e-08
Epoch 4093/5000
10/10 - 0s - 9ms/step - loss: 4.7418e-07
Epoch 4094/5000
10/10 - 0s - 9ms/step - loss: 1.4524e-07
Epoch 4095/5000
10/10 - 0s - 9ms/step - loss: 6.9773e-08
Epoch 4096/5000
10/10 - 0s - 10ms/step - loss: 1.9328e-08
Epoch 4097/5000
10/10 - 0s - 10ms/step - loss: 9.4774e-09
Epoch 4098/5000
10/10 - 0s - 9ms/step - loss: 2.5420e-09
Epoch 4099/5000
10/10 - 0s - 8ms/step - loss: 1.1347e-09
Epoch 4100/5000
10/10 - 0s - 8ms/step - loss: 2.3456e-10
Epoch 4101/5000
10/10 - 0s - 9ms/step - loss: 4.2221e-11
Epoch 4102/5000
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Epoch 4103/5000
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Epoch 4104/5000
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Epoch 4105/5000
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Epoch 4106/5000
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Epoch 4107/5000
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Epoch 4108/5000
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Epoch 4109/5000
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Epoch 4110/5000
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Epoch 4111/5000
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Epoch 4112/5000
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Epoch 4113/5000
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Epoch 4114/5000
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Epoch 4115/5000
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Epoch 4116/5000
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Epoch 4117/5000
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Epoch 4118/5000
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Epoch 4119/5000
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Epoch 4120/5000
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Epoch 4121/5000
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Epoch 4122/5000
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Epoch 4123/5000
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Epoch 4124/5000
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Epoch 4125/5000
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Epoch 4126/5000
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Epoch 4127/5000
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Epoch 4128/5000
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Epoch 4129/5000
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Epoch 4130/5000
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Epoch 4131/5000
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Epoch 4132/5000
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Epoch 4133/5000
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Epoch 4134/5000
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Epoch 4135/5000
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Epoch 4136/5000
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Epoch 4137/5000
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Epoch 4138/5000
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Epoch 4139/5000
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Epoch 4140/5000
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Epoch 4141/5000
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Epoch 4142/5000
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Epoch 4143/5000
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Epoch 4144/5000
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Epoch 4145/5000
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Epoch 4146/5000
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Epoch 4147/5000
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Epoch 4148/5000
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Epoch 4149/5000
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Epoch 4150/5000
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Epoch 4151/5000
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Epoch 4152/5000
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Epoch 4153/5000
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Epoch 4154/5000
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Epoch 4155/5000
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Epoch 4156/5000
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Epoch 4157/5000
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Epoch 4158/5000
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Epoch 4159/5000
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Epoch 4160/5000
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Epoch 4161/5000
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Epoch 4162/5000
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Epoch 4163/5000
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Epoch 4164/5000
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Epoch 4165/5000
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Epoch 4166/5000
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Epoch 4167/5000
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Epoch 4168/5000
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Epoch 4169/5000
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Epoch 4170/5000
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Epoch 4171/5000
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Epoch 4172/5000
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Epoch 4173/5000
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Epoch 4174/5000
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Epoch 4175/5000
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Epoch 4176/5000
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Epoch 4177/5000
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Epoch 4178/5000
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Epoch 4179/5000
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Epoch 4180/5000
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Epoch 4181/5000
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Epoch 4182/5000
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Epoch 4183/5000
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Epoch 4184/5000
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Epoch 4185/5000
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Epoch 4186/5000
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Epoch 4187/5000
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Epoch 4188/5000
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Epoch 4189/5000
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Epoch 4190/5000
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Epoch 4191/5000
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Epoch 4192/5000
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Epoch 4193/5000
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Epoch 4194/5000
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Epoch 4195/5000
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Epoch 4196/5000
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Epoch 4197/5000
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Epoch 4198/5000
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Epoch 4199/5000
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Epoch 4200/5000
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Epoch 4201/5000
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Epoch 4202/5000
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Epoch 4203/5000
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Epoch 4204/5000
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Epoch 4205/5000
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Epoch 4206/5000
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Epoch 4207/5000
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Epoch 4208/5000
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Epoch 4209/5000
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Epoch 4210/5000
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Epoch 4211/5000
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Epoch 4212/5000
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Epoch 4213/5000
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Epoch 4214/5000
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Epoch 4215/5000
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Epoch 4216/5000
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Epoch 4217/5000
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Epoch 4218/5000
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Epoch 4219/5000
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Epoch 4220/5000
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Epoch 4221/5000
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Epoch 4222/5000
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Epoch 4223/5000
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Epoch 4224/5000
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Epoch 4225/5000
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Epoch 4226/5000
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Epoch 4227/5000
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Epoch 4228/5000
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Epoch 4229/5000
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Epoch 4230/5000
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Epoch 4231/5000
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Epoch 4232/5000
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Epoch 4233/5000
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Epoch 4234/5000
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Epoch 4235/5000
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Epoch 4236/5000
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Epoch 4237/5000
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Epoch 4238/5000
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Epoch 4239/5000
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Epoch 4240/5000
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Epoch 4241/5000
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Epoch 4242/5000
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Epoch 4243/5000
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Epoch 4244/5000
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Epoch 4245/5000
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Epoch 4246/5000
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Epoch 4247/5000
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Epoch 4248/5000
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Epoch 4249/5000
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Epoch 4250/5000
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Epoch 4251/5000
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Epoch 4252/5000
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Epoch 4253/5000
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Epoch 4254/5000
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Epoch 4255/5000
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Epoch 4256/5000
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Epoch 4257/5000
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Epoch 4258/5000
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Epoch 4259/5000
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Epoch 4260/5000
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Epoch 4261/5000
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Epoch 4262/5000
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Epoch 4263/5000
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Epoch 4264/5000
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Epoch 4265/5000
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Epoch 4266/5000
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Epoch 4267/5000
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Epoch 4268/5000
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Epoch 4269/5000
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Epoch 4270/5000
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Epoch 4271/5000
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Epoch 4272/5000
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Epoch 4273/5000
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Epoch 4274/5000
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Epoch 4275/5000
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Epoch 4276/5000
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Epoch 4277/5000
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Epoch 4278/5000
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Epoch 4279/5000
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Epoch 4280/5000
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Epoch 4281/5000
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Epoch 4282/5000
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Epoch 4283/5000
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Epoch 4284/5000
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Epoch 4285/5000
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Epoch 4286/5000
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Epoch 4287/5000
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Epoch 4288/5000
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Epoch 4289/5000
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Epoch 4290/5000
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Epoch 4291/5000
10/10 - 0s - 10ms/step - loss: 7.7145e-08
Epoch 4292/5000
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Epoch 4293/5000
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Epoch 4294/5000
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Epoch 4295/5000
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Epoch 4296/5000
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Epoch 4297/5000
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Epoch 4298/5000
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Epoch 4299/5000
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Epoch 4300/5000
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Epoch 4301/5000
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Epoch 4302/5000
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Epoch 4303/5000
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Epoch 4304/5000
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Epoch 4305/5000
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Epoch 4306/5000
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Epoch 4307/5000
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Epoch 4308/5000
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Epoch 4309/5000
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Epoch 4310/5000
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Epoch 4311/5000
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Epoch 4312/5000
10/10 - 0s - 8ms/step - loss: 9.0815e-10
Epoch 4313/5000
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Epoch 4314/5000
10/10 - 0s - 7ms/step - loss: 7.8759e-11
Epoch 4315/5000
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Epoch 4316/5000
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Epoch 4317/5000
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Epoch 4318/5000
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Epoch 4319/5000
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Epoch 4320/5000
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Epoch 4321/5000
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Epoch 4322/5000
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Epoch 4323/5000
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Epoch 4324/5000
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Epoch 4325/5000
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Epoch 4326/5000
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Epoch 4327/5000
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Epoch 4328/5000
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Epoch 4329/5000
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Epoch 4330/5000
10/10 - 0s - 10ms/step - loss: 7.0619e-11
Epoch 4331/5000
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Epoch 4332/5000
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Epoch 4333/5000
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Epoch 4334/5000
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Epoch 4335/5000
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Epoch 4336/5000
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Epoch 4337/5000
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Epoch 4338/5000
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Epoch 4339/5000
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Epoch 4340/5000
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Epoch 4341/5000
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Epoch 4342/5000
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Epoch 4343/5000
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Epoch 4344/5000
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Epoch 4345/5000
10/10 - 0s - 8ms/step - loss: 9.2063e-09
Epoch 4346/5000
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Epoch 4347/5000
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Epoch 4348/5000
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Epoch 4349/5000
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Epoch 4350/5000
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Epoch 4351/5000
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Epoch 4352/5000
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Epoch 4353/5000
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Epoch 4354/5000
10/10 - 0s - 8ms/step - loss: 5.4463e-08
Epoch 4355/5000
10/10 - 0s - 9ms/step - loss: 1.2024e-07
Epoch 4356/5000
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Epoch 4357/5000
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Epoch 4358/5000
10/10 - 0s - 8ms/step - loss: 3.8059e-09
Epoch 4359/5000
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Epoch 4360/5000
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Epoch 4361/5000
10/10 - 0s - 9ms/step - loss: 4.2664e-08
Epoch 4362/5000
10/10 - 0s - 8ms/step - loss: 6.0421e-08
Epoch 4363/5000
10/10 - 0s - 8ms/step - loss: 3.2430e-08
Epoch 4364/5000
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Epoch 4365/5000
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Epoch 4366/5000
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Epoch 4367/5000
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Epoch 4368/5000
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Epoch 4369/5000
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Epoch 4370/5000
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Epoch 4371/5000
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Epoch 4372/5000
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Epoch 4373/5000
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Epoch 4374/5000
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Epoch 4375/5000
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Epoch 4376/5000
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Epoch 4377/5000
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Epoch 4378/5000
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Epoch 4379/5000
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Epoch 4380/5000
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Epoch 4381/5000
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Epoch 4382/5000
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Epoch 4383/5000
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Epoch 4384/5000
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Epoch 4385/5000
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Epoch 4386/5000
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Epoch 4387/5000
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Epoch 4388/5000
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Epoch 4389/5000
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Epoch 4390/5000
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Epoch 4391/5000
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Epoch 4392/5000
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Epoch 4393/5000
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Epoch 4394/5000
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Epoch 4395/5000
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Epoch 4396/5000
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Epoch 4397/5000
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Epoch 4398/5000
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Epoch 4399/5000
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Epoch 4400/5000
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Epoch 4401/5000
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Epoch 4402/5000
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Epoch 4403/5000
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Epoch 4404/5000
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Epoch 4405/5000
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Epoch 4406/5000
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Epoch 4407/5000
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Epoch 4408/5000
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Epoch 4409/5000
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Epoch 4410/5000
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Epoch 4411/5000
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Epoch 4412/5000
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Epoch 4413/5000
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Epoch 4414/5000
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Epoch 4415/5000
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Epoch 4416/5000
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Epoch 4417/5000
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Epoch 4418/5000
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Epoch 4419/5000
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Epoch 4420/5000
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Epoch 4421/5000
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Epoch 4422/5000
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Epoch 4423/5000
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Epoch 4424/5000
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Epoch 4425/5000
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Epoch 4426/5000
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Epoch 4427/5000
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Epoch 4428/5000
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Epoch 4429/5000
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Epoch 4430/5000
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Epoch 4431/5000
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Epoch 4432/5000
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Epoch 4433/5000
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Epoch 4434/5000
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Epoch 4435/5000
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Epoch 4436/5000
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Epoch 4437/5000
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Epoch 4438/5000
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Epoch 4439/5000
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Epoch 4440/5000
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Epoch 4441/5000
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Epoch 4442/5000
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Epoch 4443/5000
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Epoch 4444/5000
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Epoch 4445/5000
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Epoch 4446/5000
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Epoch 4447/5000
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Epoch 4448/5000
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Epoch 4449/5000
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Epoch 4450/5000
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Epoch 4451/5000
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Epoch 4452/5000
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Epoch 4453/5000
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Epoch 4454/5000
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Epoch 4455/5000
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Epoch 4456/5000
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Epoch 4457/5000
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Epoch 4458/5000
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Epoch 4459/5000
10/10 - 0s - 7ms/step - loss: 1.9416e-09
Epoch 4460/5000
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Epoch 4461/5000
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Epoch 4462/5000
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Epoch 4463/5000
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Epoch 4464/5000
10/10 - 0s - 14ms/step - loss: 8.8620e-09
Epoch 4465/5000
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Epoch 4466/5000
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Epoch 4467/5000
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Epoch 4468/5000
10/10 - 0s - 7ms/step - loss: 1.4362e-08
Epoch 4469/5000
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Epoch 4470/5000
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Epoch 4471/5000
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Epoch 4472/5000
10/10 - 0s - 10ms/step - loss: 3.7754e-09
Epoch 4473/5000
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Epoch 4474/5000
10/10 - 0s - 10ms/step - loss: 1.2459e-07
Epoch 4475/5000
10/10 - 0s - 9ms/step - loss: 8.5349e-08
Epoch 4476/5000
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Epoch 4477/5000
10/10 - 0s - 10ms/step - loss: 1.2240e-08
Epoch 4478/5000
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Epoch 4479/5000
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Epoch 4480/5000
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Epoch 4481/5000
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Epoch 4482/5000
10/10 - 0s - 8ms/step - loss: 7.2713e-09
Epoch 4483/5000
10/10 - 0s - 10ms/step - loss: 1.8856e-07
Epoch 4484/5000
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Epoch 4485/5000
10/10 - 0s - 9ms/step - loss: 6.1785e-08
Epoch 4486/5000
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Epoch 4487/5000
10/10 - 0s - 10ms/step - loss: 5.6526e-09
Epoch 4488/5000
10/10 - 0s - 10ms/step - loss: 2.1799e-09
Epoch 4489/5000
10/10 - 0s - 9ms/step - loss: 6.3025e-10
Epoch 4490/5000
10/10 - 0s - 9ms/step - loss: 5.9729e-11
Epoch 4491/5000
10/10 - 0s - 9ms/step - loss: 8.2873e-11
Epoch 4492/5000
10/10 - 0s - 8ms/step - loss: 4.5877e-10
Epoch 4493/5000
10/10 - 0s - 8ms/step - loss: 1.8150e-09
Epoch 4494/5000
10/10 - 0s - 10ms/step - loss: 8.0284e-10
Epoch 4495/5000
10/10 - 0s - 9ms/step - loss: 1.0384e-09
Epoch 4496/5000
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Epoch 4497/5000
10/10 - 0s - 9ms/step - loss: 2.9335e-07
Epoch 4498/5000
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Epoch 4499/5000
10/10 - 0s - 9ms/step - loss: 3.8026e-08
Epoch 4500/5000
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Epoch 4501/5000
10/10 - 0s - 9ms/step - loss: 6.1593e-09
Epoch 4502/5000
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Epoch 4503/5000
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Epoch 4504/5000
10/10 - 0s - 9ms/step - loss: 1.4218e-09
Epoch 4505/5000
10/10 - 0s - 10ms/step - loss: 3.8978e-10
Epoch 4506/5000
10/10 - 0s - 9ms/step - loss: 8.1050e-11
Epoch 4507/5000
10/10 - 0s - 8ms/step - loss: 1.9002e-09
Epoch 4508/5000
10/10 - 0s - 9ms/step - loss: 7.6608e-09
Epoch 4509/5000
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Epoch 4510/5000
10/10 - 0s - 8ms/step - loss: 1.6663e-07
Epoch 4511/5000
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Epoch 4512/5000
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Epoch 4513/5000
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Epoch 4514/5000
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Epoch 4515/5000
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Epoch 4516/5000
10/10 - 0s - 9ms/step - loss: 7.3524e-09
Epoch 4517/5000
10/10 - 0s - 9ms/step - loss: 4.4092e-08
Epoch 4518/5000
10/10 - 0s - 8ms/step - loss: 2.1362e-07
Epoch 4519/5000
10/10 - 0s - 9ms/step - loss: 4.6486e-08
Epoch 4520/5000
10/10 - 0s - 9ms/step - loss: 1.7342e-08
Epoch 4521/5000
10/10 - 0s - 9ms/step - loss: 6.7075e-09
Epoch 4522/5000
10/10 - 0s - 8ms/step - loss: 3.4265e-09
Epoch 4523/5000
10/10 - 0s - 8ms/step - loss: 4.9563e-09
Epoch 4524/5000
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Epoch 4525/5000
10/10 - 0s - 9ms/step - loss: 7.9327e-10
Epoch 4526/5000
10/10 - 0s - 8ms/step - loss: 3.3691e-09
Epoch 4527/5000
10/10 - 0s - 8ms/step - loss: 5.7717e-08
Epoch 4528/5000
10/10 - 0s - 8ms/step - loss: 2.7636e-07
Epoch 4529/5000
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Epoch 4530/5000
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Epoch 4531/5000
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Epoch 4532/5000
10/10 - 0s - 10ms/step - loss: 3.0513e-09
Epoch 4533/5000
10/10 - 0s - 9ms/step - loss: 5.2844e-10
Epoch 4534/5000
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Epoch 4535/5000
10/10 - 0s - 9ms/step - loss: 8.2748e-10
Epoch 4536/5000
10/10 - 0s - 8ms/step - loss: 4.7907e-10
Epoch 4537/5000
10/10 - 0s - 7ms/step - loss: 8.6065e-10
Epoch 4538/5000
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Epoch 4539/5000
10/10 - 0s - 10ms/step - loss: 1.5543e-08
Epoch 4540/5000
10/10 - 0s - 9ms/step - loss: 2.9687e-07
Epoch 4541/5000
10/10 - 0s - 9ms/step - loss: 1.3594e-07
Epoch 4542/5000
10/10 - 0s - 9ms/step - loss: 3.5315e-08
Epoch 4543/5000
10/10 - 0s - 7ms/step - loss: 1.2493e-08
Epoch 4544/5000
10/10 - 0s - 10ms/step - loss: 7.3358e-09
Epoch 4545/5000
10/10 - 0s - 9ms/step - loss: 1.7133e-09
Epoch 4546/5000
10/10 - 0s - 9ms/step - loss: 3.9527e-10
Epoch 4547/5000
10/10 - 0s - 8ms/step - loss: 6.8929e-10
Epoch 4548/5000
10/10 - 0s - 10ms/step - loss: 1.0591e-10
Epoch 4549/5000
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Epoch 4550/5000
10/10 - 0s - 8ms/step - loss: 4.3498e-09
Epoch 4551/5000
10/10 - 0s - 9ms/step - loss: 7.0250e-09
Epoch 4552/5000
10/10 - 0s - 9ms/step - loss: 1.4487e-08
Epoch 4553/5000
10/10 - 0s - 8ms/step - loss: 5.9355e-08
Epoch 4554/5000
10/10 - 0s - 9ms/step - loss: 1.5692e-07
Epoch 4555/5000
10/10 - 0s - 9ms/step - loss: 2.8133e-08
Epoch 4556/5000
10/10 - 0s - 10ms/step - loss: 2.4818e-08
Epoch 4557/5000
10/10 - 0s - 8ms/step - loss: 8.7916e-09
Epoch 4558/5000
10/10 - 0s - 9ms/step - loss: 6.8075e-10
Epoch 4559/5000
10/10 - 0s - 7ms/step - loss: 9.1300e-10
Epoch 4560/5000
10/10 - 0s - 8ms/step - loss: 4.9356e-10
Epoch 4561/5000
10/10 - 0s - 7ms/step - loss: 3.2092e-10
Epoch 4562/5000
10/10 - 0s - 10ms/step - loss: 8.9457e-09
Epoch 4563/5000
10/10 - 0s - 8ms/step - loss: 3.2038e-07
Epoch 4564/5000
10/10 - 0s - 8ms/step - loss: 2.7930e-07
Epoch 4565/5000
10/10 - 0s - 8ms/step - loss: 5.6222e-08
Epoch 4566/5000
10/10 - 0s - 7ms/step - loss: 3.4534e-08
Epoch 4567/5000
10/10 - 0s - 9ms/step - loss: 9.0158e-09
Epoch 4568/5000
10/10 - 0s - 8ms/step - loss: 5.4320e-09
Epoch 4569/5000
10/10 - 0s - 8ms/step - loss: 1.9069e-09
Epoch 4570/5000
10/10 - 0s - 8ms/step - loss: 1.7152e-09
Epoch 4571/5000
10/10 - 0s - 8ms/step - loss: 7.5351e-10
Epoch 4572/5000
10/10 - 0s - 9ms/step - loss: 3.1162e-10
Epoch 4573/5000
10/10 - 0s - 8ms/step - loss: 5.5986e-10
Epoch 4574/5000
10/10 - 0s - 10ms/step - loss: 7.5505e-10
Epoch 4575/5000
10/10 - 0s - 9ms/step - loss: 1.4352e-10
Epoch 4576/5000
10/10 - 0s - 10ms/step - loss: 3.2303e-11
Epoch 4577/5000
10/10 - 0s - 8ms/step - loss: 1.5029e-09
Epoch 4578/5000
10/10 - 0s - 8ms/step - loss: 1.2448e-09
Epoch 4579/5000
10/10 - 0s - 10ms/step - loss: 3.8575e-10
Epoch 4580/5000
10/10 - 0s - 9ms/step - loss: 5.9666e-10
Epoch 4581/5000
10/10 - 0s - 8ms/step - loss: 1.0575e-08
Epoch 4582/5000
10/10 - 0s - 8ms/step - loss: 2.7418e-07
Epoch 4583/5000
10/10 - 0s - 8ms/step - loss: 2.0409e-07
Epoch 4584/5000
10/10 - 0s - 7ms/step - loss: 5.2984e-08
Epoch 4585/5000
10/10 - 0s - 8ms/step - loss: 1.9128e-08
Epoch 4586/5000
10/10 - 0s - 10ms/step - loss: 9.7724e-09
Epoch 4587/5000
10/10 - 0s - 8ms/step - loss: 4.5611e-09
Epoch 4588/5000
10/10 - 0s - 9ms/step - loss: 2.1807e-09
Epoch 4589/5000
10/10 - 0s - 9ms/step - loss: 2.2823e-10
Epoch 4590/5000
10/10 - 0s - 7ms/step - loss: 7.5086e-10
Epoch 4591/5000
10/10 - 0s - 9ms/step - loss: 1.1560e-10
Epoch 4592/5000
10/10 - 0s - 8ms/step - loss: 6.9836e-10
Epoch 4593/5000
10/10 - 0s - 8ms/step - loss: 2.6887e-10
Epoch 4594/5000
10/10 - 0s - 8ms/step - loss: 4.9661e-09
Epoch 4595/5000
10/10 - 0s - 9ms/step - loss: 2.0780e-08
Epoch 4596/5000
10/10 - 0s - 9ms/step - loss: 6.0213e-08
Epoch 4597/5000
10/10 - 0s - 8ms/step - loss: 6.7676e-08
Epoch 4598/5000
10/10 - 0s - 8ms/step - loss: 4.7834e-09
Epoch 4599/5000
10/10 - 0s - 9ms/step - loss: 5.5435e-09
Epoch 4600/5000
10/10 - 0s - 18ms/step - loss: 3.4596e-08
Epoch 4601/5000
10/10 - 0s - 14ms/step - loss: 1.4042e-07
Epoch 4602/5000
10/10 - 0s - 9ms/step - loss: 3.5406e-08
Epoch 4603/5000
10/10 - 0s - 8ms/step - loss: 2.4186e-08
Epoch 4604/5000
10/10 - 0s - 8ms/step - loss: 2.3299e-09
Epoch 4605/5000
10/10 - 0s - 10ms/step - loss: 1.3105e-09
Epoch 4606/5000
10/10 - 0s - 9ms/step - loss: 1.7902e-09
Epoch 4607/5000
10/10 - 0s - 8ms/step - loss: 8.2585e-09
Epoch 4608/5000
10/10 - 0s - 8ms/step - loss: 1.0782e-07
Epoch 4609/5000
10/10 - 0s - 8ms/step - loss: 1.8651e-07
Epoch 4610/5000
10/10 - 0s - 10ms/step - loss: 4.4995e-08
Epoch 4611/5000
10/10 - 0s - 9ms/step - loss: 1.6478e-08
Epoch 4612/5000
10/10 - 0s - 9ms/step - loss: 5.1987e-09
Epoch 4613/5000
10/10 - 0s - 10ms/step - loss: 1.5232e-09
Epoch 4614/5000
10/10 - 0s - 8ms/step - loss: 2.7195e-11
Epoch 4615/5000
10/10 - 0s - 10ms/step - loss: 3.1936e-10
Epoch 4616/5000
10/10 - 0s - 9ms/step - loss: 2.1794e-09
Epoch 4617/5000
10/10 - 0s - 9ms/step - loss: 1.9178e-09
Epoch 4618/5000
10/10 - 0s - 8ms/step - loss: 2.7176e-10
Epoch 4619/5000
10/10 - 0s - 9ms/step - loss: 5.2652e-09
Epoch 4620/5000
10/10 - 0s - 8ms/step - loss: 2.4416e-07
Epoch 4621/5000
10/10 - 0s - 10ms/step - loss: 3.2308e-07
Epoch 4622/5000
10/10 - 0s - 8ms/step - loss: 7.2107e-08
Epoch 4623/5000
10/10 - 0s - 9ms/step - loss: 2.8877e-08
Epoch 4624/5000
10/10 - 0s - 8ms/step - loss: 1.0322e-08
Epoch 4625/5000
10/10 - 0s - 8ms/step - loss: 3.8210e-09
Epoch 4626/5000
10/10 - 0s - 9ms/step - loss: 2.4136e-09
Epoch 4627/5000
10/10 - 0s - 9ms/step - loss: 8.1855e-10
Epoch 4628/5000
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Epoch 4629/5000
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Epoch 4630/5000
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Epoch 4631/5000
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Epoch 4632/5000
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Epoch 4633/5000
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Epoch 4634/5000
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Epoch 4635/5000
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Epoch 4636/5000
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Epoch 4637/5000
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Epoch 4638/5000
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Epoch 4639/5000
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Epoch 4640/5000
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Epoch 4641/5000
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Epoch 4642/5000
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Epoch 4643/5000
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Epoch 4644/5000
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Epoch 4645/5000
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Epoch 4646/5000
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Epoch 4647/5000
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Epoch 4648/5000
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Epoch 4649/5000
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Epoch 4650/5000
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Epoch 4651/5000
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Epoch 4652/5000
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Epoch 4653/5000
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Epoch 4654/5000
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Epoch 4655/5000
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Epoch 4656/5000
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Epoch 4657/5000
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Epoch 4658/5000
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Epoch 4659/5000
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Epoch 4660/5000
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Epoch 4661/5000
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Epoch 4662/5000
10/10 - 0s - 9ms/step - loss: 8.4037e-10
Epoch 4663/5000
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Epoch 4664/5000
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Epoch 4665/5000
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Epoch 4666/5000
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Epoch 4667/5000
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Epoch 4668/5000
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Epoch 4669/5000
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Epoch 4670/5000
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Epoch 4671/5000
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Epoch 4672/5000
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Epoch 4673/5000
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Epoch 4674/5000
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Epoch 4675/5000
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Epoch 4676/5000
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Epoch 4677/5000
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Epoch 4678/5000
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Epoch 4679/5000
10/10 - 0s - 8ms/step - loss: 9.5736e-10
Epoch 4680/5000
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Epoch 4681/5000
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Epoch 4682/5000
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Epoch 4683/5000
10/10 - 0s - 20ms/step - loss: 6.1013e-10
Epoch 4684/5000
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Epoch 4685/5000
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Epoch 4686/5000
10/10 - 0s - 9ms/step - loss: 2.9352e-11
Epoch 4687/5000
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Epoch 4688/5000
10/10 - 0s - 7ms/step - loss: 3.8186e-09
Epoch 4689/5000
10/10 - 0s - 9ms/step - loss: 7.9185e-08
Epoch 4690/5000
10/10 - 0s - 9ms/step - loss: 3.0589e-07
Epoch 4691/5000
10/10 - 0s - 9ms/step - loss: 7.7980e-08
Epoch 4692/5000
10/10 - 0s - 8ms/step - loss: 3.6971e-08
Epoch 4693/5000
10/10 - 0s - 9ms/step - loss: 1.2231e-08
Epoch 4694/5000
10/10 - 0s - 9ms/step - loss: 2.7456e-09
Epoch 4695/5000
10/10 - 0s - 8ms/step - loss: 1.4728e-10
Epoch 4696/5000
10/10 - 0s - 18ms/step - loss: 1.7121e-11
Epoch 4697/5000
10/10 - 0s - 9ms/step - loss: 1.5900e-11
Epoch 4698/5000
10/10 - 0s - 9ms/step - loss: 2.6655e-10
Epoch 4699/5000
10/10 - 0s - 10ms/step - loss: 1.6378e-09
Epoch 4700/5000
10/10 - 0s - 9ms/step - loss: 1.0813e-09
Epoch 4701/5000
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Epoch 4702/5000
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Epoch 4703/5000
10/10 - 0s - 10ms/step - loss: 1.0623e-07
Epoch 4704/5000
10/10 - 0s - 9ms/step - loss: 1.3271e-08
Epoch 4705/5000
10/10 - 0s - 8ms/step - loss: 3.1488e-08
Epoch 4706/5000
10/10 - 0s - 9ms/step - loss: 6.3424e-09
Epoch 4707/5000
10/10 - 0s - 9ms/step - loss: 2.9826e-09
Epoch 4708/5000
10/10 - 0s - 9ms/step - loss: 1.4091e-08
Epoch 4709/5000
10/10 - 0s - 8ms/step - loss: 8.3727e-08
Epoch 4710/5000
10/10 - 0s - 8ms/step - loss: 1.3780e-07
Epoch 4711/5000
10/10 - 0s - 8ms/step - loss: 3.5770e-08
Epoch 4712/5000
10/10 - 0s - 8ms/step - loss: 1.2446e-08
Epoch 4713/5000
10/10 - 0s - 9ms/step - loss: 1.1257e-08
Epoch 4714/5000
10/10 - 0s - 8ms/step - loss: 1.0735e-08
Epoch 4715/5000
10/10 - 0s - 8ms/step - loss: 4.8667e-09
Epoch 4716/5000
10/10 - 0s - 9ms/step - loss: 2.8467e-09
Epoch 4717/5000
10/10 - 0s - 8ms/step - loss: 2.1743e-08
Epoch 4718/5000
10/10 - 0s - 10ms/step - loss: 1.5399e-07
Epoch 4719/5000
10/10 - 0s - 8ms/step - loss: 6.3171e-08
Epoch 4720/5000
10/10 - 0s - 10ms/step - loss: 3.0802e-08
Epoch 4721/5000
10/10 - 0s - 8ms/step - loss: 2.2312e-08
Epoch 4722/5000
10/10 - 0s - 9ms/step - loss: 5.3652e-09
Epoch 4723/5000
10/10 - 0s - 9ms/step - loss: 9.7103e-09
Epoch 4724/5000
10/10 - 0s - 9ms/step - loss: 3.7962e-09
Epoch 4725/5000
10/10 - 0s - 9ms/step - loss: 2.7105e-10
Epoch 4726/5000
10/10 - 0s - 23ms/step - loss: 8.1719e-10
Epoch 4727/5000
10/10 - 0s - 11ms/step - loss: 1.7578e-08
Epoch 4728/5000
10/10 - 0s - 11ms/step - loss: 2.9551e-07
Epoch 4729/5000
10/10 - 0s - 9ms/step - loss: 1.3246e-07
Epoch 4730/5000
10/10 - 0s - 9ms/step - loss: 3.9591e-08
Epoch 4731/5000
10/10 - 0s - 8ms/step - loss: 1.3780e-08
Epoch 4732/5000
10/10 - 0s - 11ms/step - loss: 6.4233e-09
Epoch 4733/5000
10/10 - 0s - 8ms/step - loss: 4.7777e-09
Epoch 4734/5000
10/10 - 0s - 9ms/step - loss: 2.3602e-09
Epoch 4735/5000
10/10 - 0s - 9ms/step - loss: 8.6739e-10
Epoch 4736/5000
10/10 - 0s - 8ms/step - loss: 3.1849e-10
Epoch 4737/5000
10/10 - 0s - 9ms/step - loss: 8.7792e-11
Epoch 4738/5000
10/10 - 0s - 9ms/step - loss: 1.4893e-10
Epoch 4739/5000
10/10 - 0s - 9ms/step - loss: 1.8215e-10
Epoch 4740/5000
10/10 - 0s - 9ms/step - loss: 1.1132e-08
Epoch 4741/5000
10/10 - 0s - 8ms/step - loss: 1.3763e-07
Epoch 4742/5000
10/10 - 0s - 8ms/step - loss: 1.2179e-07
Epoch 4743/5000
10/10 - 0s - 7ms/step - loss: 3.3023e-08
Epoch 4744/5000
10/10 - 0s - 8ms/step - loss: 9.7885e-09
Epoch 4745/5000
10/10 - 0s - 8ms/step - loss: 4.1400e-09
Epoch 4746/5000
10/10 - 0s - 10ms/step - loss: 1.3883e-09
Epoch 4747/5000
10/10 - 0s - 9ms/step - loss: 4.2749e-09
Epoch 4748/5000
10/10 - 0s - 8ms/step - loss: 8.5109e-09
Epoch 4749/5000
10/10 - 0s - 9ms/step - loss: 1.1105e-08
Epoch 4750/5000
10/10 - 0s - 9ms/step - loss: 4.5086e-08
Epoch 4751/5000
10/10 - 0s - 9ms/step - loss: 1.6715e-07
Epoch 4752/5000
10/10 - 0s - 8ms/step - loss: 3.2685e-08
Epoch 4753/5000
10/10 - 0s - 10ms/step - loss: 2.3013e-08
Epoch 4754/5000
10/10 - 0s - 8ms/step - loss: 1.6722e-08
Epoch 4755/5000
10/10 - 0s - 8ms/step - loss: 6.1112e-09
Epoch 4756/5000
10/10 - 0s - 10ms/step - loss: 1.4029e-08
Epoch 4757/5000
10/10 - 0s - 9ms/step - loss: 1.1222e-09
Epoch 4758/5000
10/10 - 0s - 8ms/step - loss: 1.6744e-11
Epoch 4759/5000
10/10 - 0s - 9ms/step - loss: 4.0249e-11
Epoch 4760/5000
10/10 - 0s - 7ms/step - loss: 9.9986e-10
Epoch 4761/5000
10/10 - 0s - 9ms/step - loss: 3.2578e-08
Epoch 4762/5000
10/10 - 0s - 8ms/step - loss: 5.3015e-07
Epoch 4763/5000
10/10 - 0s - 11ms/step - loss: 1.5688e-07
Epoch 4764/5000
10/10 - 0s - 9ms/step - loss: 5.5846e-08
Epoch 4765/5000
10/10 - 0s - 10ms/step - loss: 2.5265e-08
Epoch 4766/5000
10/10 - 0s - 9ms/step - loss: 5.9024e-09
Epoch 4767/5000
10/10 - 0s - 8ms/step - loss: 4.0925e-09
Epoch 4768/5000
10/10 - 0s - 9ms/step - loss: 2.0785e-09
Epoch 4769/5000
10/10 - 0s - 10ms/step - loss: 1.2380e-09
Epoch 4770/5000
10/10 - 0s - 9ms/step - loss: 4.5764e-10
Epoch 4771/5000
10/10 - 0s - 10ms/step - loss: 1.4516e-10
Epoch 4772/5000
10/10 - 0s - 10ms/step - loss: 2.8867e-10
Epoch 4773/5000
10/10 - 0s - 10ms/step - loss: 6.0499e-10
Epoch 4774/5000
10/10 - 0s - 9ms/step - loss: 6.1373e-10
Epoch 4775/5000
10/10 - 0s - 11ms/step - loss: 2.9336e-10
Epoch 4776/5000
10/10 - 0s - 10ms/step - loss: 3.4027e-12
Epoch 4777/5000
10/10 - 0s - 8ms/step - loss: 3.4240e-11
Epoch 4778/5000
10/10 - 0s - 9ms/step - loss: 2.5932e-10
Epoch 4779/5000
10/10 - 0s - 9ms/step - loss: 4.6187e-09
Epoch 4780/5000
10/10 - 0s - 8ms/step - loss: 1.7424e-08
Epoch 4781/5000
10/10 - 0s - 9ms/step - loss: 7.3825e-08
Epoch 4782/5000
10/10 - 0s - 10ms/step - loss: 1.0930e-07
Epoch 4783/5000
10/10 - 0s - 22ms/step - loss: 1.6063e-08
Epoch 4784/5000
10/10 - 0s - 9ms/step - loss: 9.8917e-09
Epoch 4785/5000
10/10 - 0s - 8ms/step - loss: 1.0332e-08
Epoch 4786/5000
10/10 - 0s - 8ms/step - loss: 3.4324e-09
Epoch 4787/5000
10/10 - 0s - 8ms/step - loss: 3.9174e-09
Epoch 4788/5000
10/10 - 0s - 8ms/step - loss: 3.9987e-08
Epoch 4789/5000
10/10 - 0s - 9ms/step - loss: 1.7395e-07
Epoch 4790/5000
10/10 - 0s - 9ms/step - loss: 4.7952e-08
Epoch 4791/5000
10/10 - 0s - 8ms/step - loss: 2.4156e-08
Epoch 4792/5000
10/10 - 0s - 9ms/step - loss: 7.3150e-09
Epoch 4793/5000
10/10 - 0s - 8ms/step - loss: 1.0682e-09
Epoch 4794/5000
10/10 - 0s - 10ms/step - loss: 1.0299e-10
Epoch 4795/5000
10/10 - 0s - 9ms/step - loss: 6.9858e-11
Epoch 4796/5000
10/10 - 0s - 9ms/step - loss: 4.3300e-10
Epoch 4797/5000
10/10 - 0s - 8ms/step - loss: 1.1632e-10
Epoch 4798/5000
10/10 - 0s - 8ms/step - loss: 9.8554e-09
Epoch 4799/5000
10/10 - 0s - 7ms/step - loss: 3.7747e-07
Epoch 4800/5000
10/10 - 0s - 8ms/step - loss: 2.3989e-07
Epoch 4801/5000
10/10 - 0s - 9ms/step - loss: 6.3127e-08
Epoch 4802/5000
10/10 - 0s - 9ms/step - loss: 3.0767e-08
Epoch 4803/5000
10/10 - 0s - 10ms/step - loss: 8.1143e-09
Epoch 4804/5000
10/10 - 0s - 7ms/step - loss: 2.4795e-09
Epoch 4805/5000
10/10 - 0s - 9ms/step - loss: 1.1011e-09
Epoch 4806/5000
10/10 - 0s - 8ms/step - loss: 4.8226e-10
Epoch 4807/5000
10/10 - 0s - 9ms/step - loss: 3.9107e-10
Epoch 4808/5000
10/10 - 0s - 9ms/step - loss: 2.0391e-10
Epoch 4809/5000
10/10 - 0s - 9ms/step - loss: 2.6001e-10
Epoch 4810/5000
10/10 - 0s - 9ms/step - loss: 1.4507e-10
Epoch 4811/5000
10/10 - 0s - 9ms/step - loss: 2.5278e-10
Epoch 4812/5000
10/10 - 0s - 9ms/step - loss: 1.9330e-10
Epoch 4813/5000
10/10 - 0s - 10ms/step - loss: 3.8497e-10
Epoch 4814/5000
10/10 - 0s - 10ms/step - loss: 1.3295e-10
Epoch 4815/5000
10/10 - 0s - 9ms/step - loss: 3.9588e-09
Epoch 4816/5000
10/10 - 0s - 8ms/step - loss: 2.4665e-08
Epoch 4817/5000
10/10 - 0s - 9ms/step - loss: 1.1963e-07
Epoch 4818/5000
10/10 - 0s - 8ms/step - loss: 5.3017e-08
Epoch 4819/5000
10/10 - 0s - 9ms/step - loss: 2.8955e-08
Epoch 4820/5000
10/10 - 0s - 9ms/step - loss: 3.6819e-09
Epoch 4821/5000
10/10 - 0s - 8ms/step - loss: 4.8796e-09
Epoch 4822/5000
10/10 - 0s - 8ms/step - loss: 9.7179e-10
Epoch 4823/5000
10/10 - 0s - 9ms/step - loss: 9.8408e-09
Epoch 4824/5000
10/10 - 0s - 18ms/step - loss: 7.9410e-08
Epoch 4825/5000
10/10 - 0s - 8ms/step - loss: 1.6956e-07
Epoch 4826/5000
10/10 - 0s - 8ms/step - loss: 3.4608e-08
Epoch 4827/5000
10/10 - 0s - 9ms/step - loss: 1.0145e-08
Epoch 4828/5000
10/10 - 0s - 9ms/step - loss: 4.9672e-09
Epoch 4829/5000
10/10 - 0s - 10ms/step - loss: 1.8321e-09
Epoch 4830/5000
10/10 - 0s - 9ms/step - loss: 6.8340e-10
Epoch 4831/5000
10/10 - 0s - 8ms/step - loss: 3.1657e-09
Epoch 4832/5000
10/10 - 0s - 9ms/step - loss: 2.9600e-08
Epoch 4833/5000
10/10 - 0s - 9ms/step - loss: 1.5840e-07
Epoch 4834/5000
10/10 - 0s - 10ms/step - loss: 4.2260e-08
Epoch 4835/5000
10/10 - 0s - 8ms/step - loss: 2.4646e-08
Epoch 4836/5000
10/10 - 0s - 9ms/step - loss: 1.0471e-08
Epoch 4837/5000
10/10 - 0s - 7ms/step - loss: 1.3824e-09
Epoch 4838/5000
10/10 - 0s - 8ms/step - loss: 1.2636e-08
Epoch 4839/5000
10/10 - 0s - 8ms/step - loss: 2.5283e-08
Epoch 4840/5000
10/10 - 0s - 19ms/step - loss: 3.6621e-08
Epoch 4841/5000
10/10 - 0s - 10ms/step - loss: 4.2689e-08
Epoch 4842/5000
10/10 - 0s - 10ms/step - loss: 3.7246e-08
Epoch 4843/5000
10/10 - 0s - 8ms/step - loss: 2.7647e-08
Epoch 4844/5000
10/10 - 0s - 8ms/step - loss: 1.8674e-08
Epoch 4845/5000
10/10 - 0s - 8ms/step - loss: 8.7513e-09
Epoch 4846/5000
10/10 - 0s - 8ms/step - loss: 6.3602e-08
Epoch 4847/5000
10/10 - 0s - 20ms/step - loss: 1.8756e-07
Epoch 4848/5000
10/10 - 0s - 17ms/step - loss: 4.2387e-08
Epoch 4849/5000
10/10 - 0s - 10ms/step - loss: 1.5900e-08
Epoch 4850/5000
10/10 - 0s - 10ms/step - loss: 5.9376e-09
Epoch 4851/5000
10/10 - 0s - 12ms/step - loss: 2.6908e-09
Epoch 4852/5000
10/10 - 0s - 11ms/step - loss: 3.3650e-09
Epoch 4853/5000
10/10 - 0s - 11ms/step - loss: 7.3192e-10
Epoch 4854/5000
10/10 - 0s - 9ms/step - loss: 3.2525e-10
Epoch 4855/5000
10/10 - 0s - 10ms/step - loss: 1.1722e-09
Epoch 4856/5000
10/10 - 0s - 9ms/step - loss: 2.7543e-08
Epoch 4857/5000
10/10 - 0s - 17ms/step - loss: 3.4283e-07
Epoch 4858/5000
10/10 - 0s - 10ms/step - loss: 9.0135e-08
Epoch 4859/5000
10/10 - 0s - 9ms/step - loss: 2.6731e-08
Epoch 4860/5000
10/10 - 0s - 8ms/step - loss: 1.3044e-08
Epoch 4861/5000
10/10 - 0s - 8ms/step - loss: 5.9139e-09
Epoch 4862/5000
10/10 - 0s - 11ms/step - loss: 9.1570e-10
Epoch 4863/5000
10/10 - 0s - 11ms/step - loss: 7.1994e-11
Epoch 4864/5000
10/10 - 0s - 9ms/step - loss: 9.3038e-10
Epoch 4865/5000
10/10 - 0s - 10ms/step - loss: 1.2082e-10
Epoch 4866/5000
10/10 - 0s - 10ms/step - loss: 1.6174e-10
Epoch 4867/5000
10/10 - 0s - 9ms/step - loss: 3.5877e-10
Epoch 4868/5000
10/10 - 0s - 10ms/step - loss: 1.2324e-09
Epoch 4869/5000
10/10 - 0s - 9ms/step - loss: 7.7273e-10
Epoch 4870/5000
10/10 - 0s - 9ms/step - loss: 1.1151e-08
Epoch 4871/5000
10/10 - 0s - 9ms/step - loss: 2.5763e-07
Epoch 4872/5000
10/10 - 0s - 9ms/step - loss: 1.4582e-07
Epoch 4873/5000
10/10 - 0s - 10ms/step - loss: 4.1309e-08
Epoch 4874/5000
10/10 - 0s - 18ms/step - loss: 1.1593e-08
Epoch 4875/5000
10/10 - 0s - 17ms/step - loss: 4.6798e-09
Epoch 4876/5000
10/10 - 0s - 10ms/step - loss: 2.7344e-09
Epoch 4877/5000
10/10 - 0s - 17ms/step - loss: 1.6107e-09
Epoch 4878/5000
10/10 - 0s - 10ms/step - loss: 8.0981e-10
Epoch 4879/5000
10/10 - 0s - 9ms/step - loss: 2.0637e-10
Epoch 4880/5000
10/10 - 0s - 8ms/step - loss: 1.6733e-10
Epoch 4881/5000
10/10 - 0s - 9ms/step - loss: 4.6437e-11
Epoch 4882/5000
10/10 - 0s - 9ms/step - loss: 1.9079e-10
Epoch 4883/5000
10/10 - 0s - 11ms/step - loss: 3.0058e-09
Epoch 4884/5000
10/10 - 0s - 9ms/step - loss: 2.7870e-08
Epoch 4885/5000
10/10 - 0s - 12ms/step - loss: 3.3722e-07
Epoch 4886/5000
10/10 - 0s - 13ms/step - loss: 9.5162e-08
Epoch 4887/5000
10/10 - 0s - 8ms/step - loss: 2.9677e-08
Epoch 4888/5000
10/10 - 0s - 9ms/step - loss: 1.4953e-08
Epoch 4889/5000
10/10 - 0s - 9ms/step - loss: 8.8060e-09
Epoch 4890/5000
10/10 - 0s - 9ms/step - loss: 2.8657e-09
Epoch 4891/5000
10/10 - 0s - 9ms/step - loss: 8.9674e-10
Epoch 4892/5000
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Epoch 4893/5000
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Epoch 4894/5000
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Epoch 4895/5000
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Epoch 4896/5000
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Epoch 4897/5000
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Epoch 4898/5000
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Epoch 4899/5000
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Epoch 4900/5000
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Epoch 4901/5000
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Epoch 4902/5000
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Epoch 4903/5000
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Epoch 4904/5000
10/10 - 0s - 7ms/step - loss: 9.2826e-08
Epoch 4905/5000
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Epoch 4906/5000
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Epoch 4907/5000
10/10 - 0s - 8ms/step - loss: 7.4846e-09
Epoch 4908/5000
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Epoch 4909/5000
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Epoch 4910/5000
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Epoch 4911/5000
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Epoch 4912/5000
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Epoch 4913/5000
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Epoch 4914/5000
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Epoch 4915/5000
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Epoch 4916/5000
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Epoch 4917/5000
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Epoch 4918/5000
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Epoch 4919/5000
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Epoch 4920/5000
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Epoch 4921/5000
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Epoch 4922/5000
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Epoch 4923/5000
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Epoch 4924/5000
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Epoch 4925/5000
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Epoch 4926/5000
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Epoch 4927/5000
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Epoch 4928/5000
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Epoch 4929/5000
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Epoch 4930/5000
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Epoch 4931/5000
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Epoch 4932/5000
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Epoch 4933/5000
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Epoch 4934/5000
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Epoch 4935/5000
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Epoch 4936/5000
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Epoch 4937/5000
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Epoch 4938/5000
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Epoch 4939/5000
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Epoch 4940/5000
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Epoch 4941/5000
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Epoch 4942/5000
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Epoch 4943/5000
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Epoch 4944/5000
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Epoch 4945/5000
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Epoch 4946/5000
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Epoch 4947/5000
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Epoch 4948/5000
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Epoch 4949/5000
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Epoch 4950/5000
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Epoch 4951/5000
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Epoch 4952/5000
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Epoch 4953/5000
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Epoch 4954/5000
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Epoch 4955/5000
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Epoch 4956/5000
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Epoch 4957/5000
10/10 - 0s - 9ms/step - loss: 4.3918e-10
Epoch 4958/5000
10/10 - 0s - 9ms/step - loss: 3.5041e-09
Epoch 4959/5000
10/10 - 0s - 10ms/step - loss: 7.0783e-08
Epoch 4960/5000
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Epoch 4961/5000
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Epoch 4962/5000
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Epoch 4963/5000
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Epoch 4964/5000
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Epoch 4965/5000
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Epoch 4966/5000
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Epoch 4967/5000
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Epoch 4968/5000
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Epoch 4969/5000
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Epoch 4970/5000
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Epoch 4971/5000
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Epoch 4972/5000
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Epoch 4973/5000
10/10 - 0s - 9ms/step - loss: 6.6408e-09
Epoch 4974/5000
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Epoch 4975/5000
10/10 - 0s - 9ms/step - loss: 6.0968e-10
Epoch 4976/5000
10/10 - 0s - 8ms/step - loss: 3.5264e-09
Epoch 4977/5000
10/10 - 0s - 9ms/step - loss: 2.6916e-08
Epoch 4978/5000
10/10 - 0s - 8ms/step - loss: 2.4418e-07
Epoch 4979/5000
10/10 - 0s - 9ms/step - loss: 8.9262e-08
Epoch 4980/5000
10/10 - 0s - 10ms/step - loss: 3.2003e-08
Epoch 4981/5000
10/10 - 0s - 8ms/step - loss: 1.6487e-08
Epoch 4982/5000
10/10 - 0s - 8ms/step - loss: 7.2434e-09
Epoch 4983/5000
10/10 - 0s - 10ms/step - loss: 3.2508e-09
Epoch 4984/5000
10/10 - 0s - 8ms/step - loss: 2.5635e-09
Epoch 4985/5000
10/10 - 0s - 8ms/step - loss: 2.7063e-09
Epoch 4986/5000
10/10 - 0s - 8ms/step - loss: 3.4893e-09
Epoch 4987/5000
10/10 - 0s - 10ms/step - loss: 6.7564e-09
Epoch 4988/5000
10/10 - 0s - 9ms/step - loss: 4.8955e-09
Epoch 4989/5000
10/10 - 0s - 9ms/step - loss: 3.7655e-08
Epoch 4990/5000
10/10 - 0s - 8ms/step - loss: 1.8851e-07
Epoch 4991/5000
10/10 - 0s - 8ms/step - loss: 4.4480e-08
Epoch 4992/5000
10/10 - 0s - 8ms/step - loss: 2.1943e-08
Epoch 4993/5000
10/10 - 0s - 7ms/step - loss: 8.4140e-09
Epoch 4994/5000
10/10 - 0s - 9ms/step - loss: 2.7586e-09
Epoch 4995/5000
10/10 - 0s - 10ms/step - loss: 4.9227e-10
Epoch 4996/5000
10/10 - 0s - 9ms/step - loss: 4.7828e-11
Epoch 4997/5000
10/10 - 0s - 8ms/step - loss: 6.4106e-11
Epoch 4998/5000
10/10 - 0s - 11ms/step - loss: 3.0552e-10
Epoch 4999/5000
10/10 - 0s - 8ms/step - loss: 1.9043e-08
Epoch 5000/5000
10/10 - 0s - 9ms/step - loss: 3.4603e-07
1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 242ms/step